In this research, a model free sliding mode fuzzy adaptive inverse dynamic fuzzy controller (SMFIDFC) is designed for a robot manipulator to rich the best performance. Inverse dynamic controller is considered because of its high performance in certain system. Fuzzy methodology has been included in inverse dynamic to keep away from design nonlinear controller based on dynamic model. Sliding mode fuzzy adaptive methodology is applied to model free controller to have better result in presence of structure and unstructured uncertainties. Besides, this control method can be applied to non-linear systems easily. Today, strong mathematical tools are used in new control methodologies to design adaptive nonlinear controller with satisfactory output results (e.g., minimum error, good trajectory, disturbance rejection).
Design Novel Nonlinear Controller Applied to Robot Manipulator: Design New Fe...Waqas Tariq
In this paper, fuzzy adaptive base tuning feedback linearization fuzzy methodology to adaption gain is introduced. The system performance in feedback linearization controller and feedback linearization fuzzy controller are sensitive to the main controller coefficient. Therefore, compute the optimum value of main controller coefficient for a system is the main important challenge work. This problem has solved by adjusting main fuzzy controller continuously in real-time. In this way, the overall system performance has improved with respect to the classical feedback linearization controller and feedback linearization fuzzy controller. Adaptive feedback linearization fuzzy controller solved external disturbance as well as mathematical nonlinear equivalent part by applied fuzzy supervisory method in feedback linearization fuzzy controller. The addition of an adaptive law to a feedback linearization fuzzy controller to online tune the parameters of the fuzzy rules in use will ensure a moderate computational load. Refer to this research; tuning methodology can online adjust coefficient parts of the fuzzy rules. Since this algorithm for is specifically applied to a robot manipulator.
A New Estimate Sliding Mode Fuzzy Controller for Robotic ManipulatorWaqas Tariq
One of the most active research areas in field of robotics is control of robot manipulator because this system has highly nonlinear dynamic parameters and most of dynamic parameters are unknown so design an acceptable controller is the main goal in this work. To solve this challenge position new estimation sliding mode fuzzy controller is introduced and applied to robot manipulator. This controller can solve to most important challenge in classical sliding mode controller in presence of highly uncertainty, namely; chattering phenomenon based on fuzzy estimator and online tuning and equivalent nonlinear dynamic based on estimation. Proposed method has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 s, steady state error = 1e-9 and RMS error=0.0001632).
Design a nonlinear controller for second order nonlinear uncertain dynamical systems (e.g., Internal Combustion Engine) is one of the most important challenging works. This paper focuses on the design of a robust backstepping adaptive feedback linearization controller (FLC) for internal combustion (IC) engine in presence of uncertainties. In order to provide high performance nonlinear methodology, feedback linearization controller is selected. Pure feedback linearization controller can be used to control of partly unknown nonlinear dynamic parameters of IC engine. In order to solve the uncertain nonlinear dynamic parameters, implement easily and avoid mathematical model base controller, Mamdani’s performance/error-based fuzzy logic methodology with two inputs and one output and 49 rules is applied to pure feedback linearization controller. The results demonstrate that the error-based fuzzy feedback linearization controller is a model-free controllers which works well in certain and partly uncertain system. Pure feedback linearization controller and error-based feedback linearization like controller with have difficulty in handling unstructured model uncertainties. To solve this problem applied backstepping-based tuning method to error-based fuzzy feedback linearization controller for adjusting the feedback linearization controller gain (K_p,K_v ). This controller has acceptable performance in presence of uncertainty (e.g., overshoot=1%, rise time=0.48 second, steady state error = 1.3e-9 and RMS error=1.8e-11).
Refer to the research, design a novel SISO adaptive fuzzy sliding algorithm inverse dynamic like method (NAIDLC) and application to robot manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in inverse dynamic controller, fuzzy logic controller and self tuning fuzzy sliding method, the output has improved. The main objective in this research is analyses and design of the adaptive robust controller based on artificial intelligence and nonlinear control. Robot manipulator is nonlinear, time variant and a number of parameters are uncertain, so design the best controller for this plant is the main target. Although inverse dynamic controller have acceptable performance with known dynamic parameters but regarding to uncertainty, this controller\'s output has fairly fluctuations. In order to solve this problem this research is focoused on two methodology the first one is design a fuzzy inference system as a estimate nonlinear part of main controller but this method caused to high computation load in fuzzy rule base and the second method is focused on design novel adaptive method to reduce the computation in fuzzy algorithm.
Evaluation Performance of 2nd Order Nonlinear System: Baseline Control Tunabl...Waqas Tariq
Design a nonlinear controller for second order nonlinear uncertain dynamical systems (e.g., internal combustion engine) is one of the most important challenging works. This paper focuses on the comparative study between two important nonlinear controllers namely; computed torque controller (CTC) and sliding mode controller (SMC) and applied to internal combustion (IC) engine in presence of uncertainties. In order to provide high performance nonlinear methodology, sliding mode controller and computed torque controller are selected. Pure SMC and CTC can be used to control of partly known nonlinear dynamic parameters of IC engine. Pure sliding mode controller and computed torque controller have difficulty in handling unstructured model uncertainties. To solve this problem applied linear error-based tuning method to sliding mode controller and computed torque controller for adjusting the sliding surface gain (ë ) and linear inner loop gain (K). Since the sliding surface gain (ë) and linear inner loop gain (K) are adjusted by linear error-based tuning method. In this research new ë and new K are obtained by the previous ë and K multiple gains updating factor(á). The results demonstrate that the error-based linear SMC and CTC are model-based controllers which works well in certain and uncertain system. These controllers have acceptable performance in presence of uncertainty.
Methodology of Mathematical error-Based Tuning Sliding Mode ControllerCSCJournals
Design a nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This paper focuses on the design of a chattering free mathematical error-based tuning sliding mode controller (MTSMC) for highly nonlinear dynamic robot manipulator, in presence of uncertainties. In order to provide high performance nonlinear methodology, sliding mode controller is selected. Pure sliding mode controller can be used to control of partly known nonlinear dynamic parameters of robot manipulator. Conversely, pure sliding mode controller is used in many applications; it has an important drawback namely; chattering phenomenon which it can causes some problems such as saturation and heat the mechanical parts of robot manipulators or drivers. In order to reduce the chattering this research is used the switching function in presence of mathematical error-based method instead of switching function method in pure sliding mode controller. The results demonstrate that the sliding mode controller with switching function is a model-based controllers which works well in certain and partly uncertain system. Pure sliding mode controller has difficulty in handling unstructured model uncertainties. To solve this problem applied mathematical model-free tuning method to sliding mode controller for adjusting the sliding surface gain (ë ). Since the sliding surface gain (ë) is adjusted by mathematical model free-based tuning method, it is nonlinear and continuous. In this research new ë is obtained by the previous ë multiple sliding surface slopes updating factor (á). Chattering free mathematical error-based tuning sliding mode controller is stable controller which eliminates the chattering phenomenon without to use the boundary layer saturation function. Lyapunov stability is proved in mathematical error-based tuning sliding mode controller with switching (sign) function. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 second, steady state error = 1e-9 and RMS error=1.8e-12).
Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC with Tun...Waqas Tariq
One of the most active research areas in the field of robotics is robot manipulators control, because these systems are multi-input multi-output (MIMO), nonlinear, time variant and uncertainty. An artificial non linear robust controller design is major subject in this work. At present, robot manipulators are used in unknown and unstructured situation and caused to provide complicated systems, consequently nonlinear classical controllers are used in artificial intelligence control methodologies to design nonlinear robust controller with satisfactory performance (e.g., minimum error, good trajectory, disturbance rejection). Sliding mode controller (SMC) and computed torque controller (CTC) are the best nonlinear robust controllers which can be used in uncertainty nonlinear. Sliding mode controller has two most important challenges in uncertain systems: chattering phenomenon and nonlinear dynamic equivalent part. Computed torque controller works very well when all nonlinear dynamic parameters are known. This research is focused on the applied non-classical method (e.g., Fuzzy Logic) in robust classical method (e.g., Sliding Mode Controller and computed torque controller) in the presence of uncertainties and external disturbance to reduce the limitations. Applying the Mamdani’s error based fuzzy logic controller with minimum rules is the first goal that causes the elimination of the mathematical nonlinear dynamic in SMC and CTC. Second target focuses on the elimination of chattering phenomenon with regard to the variety of uncertainty and external disturbance in fuzzy sliding mode controller and computed torque like controller by optimization the tunable gain. Therefore fuzzy sliding mode controller with tunable gain (GTFSMC) and computed torque like controller with tunable gain (GTCTLC) will be presented in this paper.
Design Auto Adjust Sliding Surface Slope: Applied to Robot ManipulatorWaqas Tariq
The main target in this paper is to present the nonlinear methods in order to control the robot manipulators and also the related results. Also the important role of sliding surface slope in sliding mode fuzzy control of robot manipulator should be considered. Sliding mode controller (SMC) is a significant nonlinear controller in certain and uncertain dynamic parameters systems. To solve the chattering phenomenon, this paper complicated two methods to each other; boundary layer method and applied fuzzy logic in sliding mode methodology. To remove the chattering sliding surface slope also played important role so this paper focused on the auto tuning this important coefficient to have the best results by applied mathematical model free methodology. Auto tuning methodology has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 s, steady state error = 1e-9 and RMS error=0.0001632).
Design Novel Nonlinear Controller Applied to Robot Manipulator: Design New Fe...Waqas Tariq
In this paper, fuzzy adaptive base tuning feedback linearization fuzzy methodology to adaption gain is introduced. The system performance in feedback linearization controller and feedback linearization fuzzy controller are sensitive to the main controller coefficient. Therefore, compute the optimum value of main controller coefficient for a system is the main important challenge work. This problem has solved by adjusting main fuzzy controller continuously in real-time. In this way, the overall system performance has improved with respect to the classical feedback linearization controller and feedback linearization fuzzy controller. Adaptive feedback linearization fuzzy controller solved external disturbance as well as mathematical nonlinear equivalent part by applied fuzzy supervisory method in feedback linearization fuzzy controller. The addition of an adaptive law to a feedback linearization fuzzy controller to online tune the parameters of the fuzzy rules in use will ensure a moderate computational load. Refer to this research; tuning methodology can online adjust coefficient parts of the fuzzy rules. Since this algorithm for is specifically applied to a robot manipulator.
A New Estimate Sliding Mode Fuzzy Controller for Robotic ManipulatorWaqas Tariq
One of the most active research areas in field of robotics is control of robot manipulator because this system has highly nonlinear dynamic parameters and most of dynamic parameters are unknown so design an acceptable controller is the main goal in this work. To solve this challenge position new estimation sliding mode fuzzy controller is introduced and applied to robot manipulator. This controller can solve to most important challenge in classical sliding mode controller in presence of highly uncertainty, namely; chattering phenomenon based on fuzzy estimator and online tuning and equivalent nonlinear dynamic based on estimation. Proposed method has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 s, steady state error = 1e-9 and RMS error=0.0001632).
Design a nonlinear controller for second order nonlinear uncertain dynamical systems (e.g., Internal Combustion Engine) is one of the most important challenging works. This paper focuses on the design of a robust backstepping adaptive feedback linearization controller (FLC) for internal combustion (IC) engine in presence of uncertainties. In order to provide high performance nonlinear methodology, feedback linearization controller is selected. Pure feedback linearization controller can be used to control of partly unknown nonlinear dynamic parameters of IC engine. In order to solve the uncertain nonlinear dynamic parameters, implement easily and avoid mathematical model base controller, Mamdani’s performance/error-based fuzzy logic methodology with two inputs and one output and 49 rules is applied to pure feedback linearization controller. The results demonstrate that the error-based fuzzy feedback linearization controller is a model-free controllers which works well in certain and partly uncertain system. Pure feedback linearization controller and error-based feedback linearization like controller with have difficulty in handling unstructured model uncertainties. To solve this problem applied backstepping-based tuning method to error-based fuzzy feedback linearization controller for adjusting the feedback linearization controller gain (K_p,K_v ). This controller has acceptable performance in presence of uncertainty (e.g., overshoot=1%, rise time=0.48 second, steady state error = 1.3e-9 and RMS error=1.8e-11).
Refer to the research, design a novel SISO adaptive fuzzy sliding algorithm inverse dynamic like method (NAIDLC) and application to robot manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in inverse dynamic controller, fuzzy logic controller and self tuning fuzzy sliding method, the output has improved. The main objective in this research is analyses and design of the adaptive robust controller based on artificial intelligence and nonlinear control. Robot manipulator is nonlinear, time variant and a number of parameters are uncertain, so design the best controller for this plant is the main target. Although inverse dynamic controller have acceptable performance with known dynamic parameters but regarding to uncertainty, this controller\'s output has fairly fluctuations. In order to solve this problem this research is focoused on two methodology the first one is design a fuzzy inference system as a estimate nonlinear part of main controller but this method caused to high computation load in fuzzy rule base and the second method is focused on design novel adaptive method to reduce the computation in fuzzy algorithm.
Evaluation Performance of 2nd Order Nonlinear System: Baseline Control Tunabl...Waqas Tariq
Design a nonlinear controller for second order nonlinear uncertain dynamical systems (e.g., internal combustion engine) is one of the most important challenging works. This paper focuses on the comparative study between two important nonlinear controllers namely; computed torque controller (CTC) and sliding mode controller (SMC) and applied to internal combustion (IC) engine in presence of uncertainties. In order to provide high performance nonlinear methodology, sliding mode controller and computed torque controller are selected. Pure SMC and CTC can be used to control of partly known nonlinear dynamic parameters of IC engine. Pure sliding mode controller and computed torque controller have difficulty in handling unstructured model uncertainties. To solve this problem applied linear error-based tuning method to sliding mode controller and computed torque controller for adjusting the sliding surface gain (ë ) and linear inner loop gain (K). Since the sliding surface gain (ë) and linear inner loop gain (K) are adjusted by linear error-based tuning method. In this research new ë and new K are obtained by the previous ë and K multiple gains updating factor(á). The results demonstrate that the error-based linear SMC and CTC are model-based controllers which works well in certain and uncertain system. These controllers have acceptable performance in presence of uncertainty.
Methodology of Mathematical error-Based Tuning Sliding Mode ControllerCSCJournals
Design a nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This paper focuses on the design of a chattering free mathematical error-based tuning sliding mode controller (MTSMC) for highly nonlinear dynamic robot manipulator, in presence of uncertainties. In order to provide high performance nonlinear methodology, sliding mode controller is selected. Pure sliding mode controller can be used to control of partly known nonlinear dynamic parameters of robot manipulator. Conversely, pure sliding mode controller is used in many applications; it has an important drawback namely; chattering phenomenon which it can causes some problems such as saturation and heat the mechanical parts of robot manipulators or drivers. In order to reduce the chattering this research is used the switching function in presence of mathematical error-based method instead of switching function method in pure sliding mode controller. The results demonstrate that the sliding mode controller with switching function is a model-based controllers which works well in certain and partly uncertain system. Pure sliding mode controller has difficulty in handling unstructured model uncertainties. To solve this problem applied mathematical model-free tuning method to sliding mode controller for adjusting the sliding surface gain (ë ). Since the sliding surface gain (ë) is adjusted by mathematical model free-based tuning method, it is nonlinear and continuous. In this research new ë is obtained by the previous ë multiple sliding surface slopes updating factor (á). Chattering free mathematical error-based tuning sliding mode controller is stable controller which eliminates the chattering phenomenon without to use the boundary layer saturation function. Lyapunov stability is proved in mathematical error-based tuning sliding mode controller with switching (sign) function. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 second, steady state error = 1e-9 and RMS error=1.8e-12).
Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC with Tun...Waqas Tariq
One of the most active research areas in the field of robotics is robot manipulators control, because these systems are multi-input multi-output (MIMO), nonlinear, time variant and uncertainty. An artificial non linear robust controller design is major subject in this work. At present, robot manipulators are used in unknown and unstructured situation and caused to provide complicated systems, consequently nonlinear classical controllers are used in artificial intelligence control methodologies to design nonlinear robust controller with satisfactory performance (e.g., minimum error, good trajectory, disturbance rejection). Sliding mode controller (SMC) and computed torque controller (CTC) are the best nonlinear robust controllers which can be used in uncertainty nonlinear. Sliding mode controller has two most important challenges in uncertain systems: chattering phenomenon and nonlinear dynamic equivalent part. Computed torque controller works very well when all nonlinear dynamic parameters are known. This research is focused on the applied non-classical method (e.g., Fuzzy Logic) in robust classical method (e.g., Sliding Mode Controller and computed torque controller) in the presence of uncertainties and external disturbance to reduce the limitations. Applying the Mamdani’s error based fuzzy logic controller with minimum rules is the first goal that causes the elimination of the mathematical nonlinear dynamic in SMC and CTC. Second target focuses on the elimination of chattering phenomenon with regard to the variety of uncertainty and external disturbance in fuzzy sliding mode controller and computed torque like controller by optimization the tunable gain. Therefore fuzzy sliding mode controller with tunable gain (GTFSMC) and computed torque like controller with tunable gain (GTCTLC) will be presented in this paper.
Design Auto Adjust Sliding Surface Slope: Applied to Robot ManipulatorWaqas Tariq
The main target in this paper is to present the nonlinear methods in order to control the robot manipulators and also the related results. Also the important role of sliding surface slope in sliding mode fuzzy control of robot manipulator should be considered. Sliding mode controller (SMC) is a significant nonlinear controller in certain and uncertain dynamic parameters systems. To solve the chattering phenomenon, this paper complicated two methods to each other; boundary layer method and applied fuzzy logic in sliding mode methodology. To remove the chattering sliding surface slope also played important role so this paper focused on the auto tuning this important coefficient to have the best results by applied mathematical model free methodology. Auto tuning methodology has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 s, steady state error = 1e-9 and RMS error=0.0001632).
Design Error-based Linear Model-free Evaluation Performance Computed Torque C...Waqas Tariq
Design a nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This research focuses on the design, implementation and analysis of a model-free linear error-based tuning computed torque controller for highly nonlinear dynamic second order system, in presence of uncertainties. In order to provide high performance nonlinear methodology, computed torque controller is selected. Pure computed torque controller can be used to control of partly known nonlinear dynamic parameters of nonlinear systems. Conversely, pure computed torque controller is used in many applications; it has an important drawback namely; nonlinear equivalent dynamic formulation in uncertain dynamic parameter. In order to solve the uncertain nonlinear dynamic parameters, implement easily and avoid mathematical model base controller, model-free performance/error-based linear methodology with three inputs and one output is applied to pure computed torque controller. The results demonstrate that the error-based linear tuning computed torque controller is a model-based controllers which works well in certain and uncertain system. Pure computed torque controller has difficulty in handling unstructured model uncertainties. To solve this problem applied linear model-free error -based tuning method to computed torque controller for adjusting the linear inner loop gain (K ). Since the linear inner loop gain (K) is adjusted by linear error-based tuning method, it is linear and continuous. In this research new K is obtained by the previous K multiple gain updating factor (á) which is a coefficient varies between half to two.
The developed control methodology can be used to build more efficient intelligent and precision mechatronic systems. Three degrees of freedom robot arm is controlled by adaptive sliding mode fuzzy algorithm fuzzy sliding mode controller (SMFAFSMC). This plant has 3 revolute joints allowing the corresponding links to move horizontally. Control of robotic manipulator is very important in field of robotic, because robotic manipulators are Multi-Input Multi-Output (MIMO), nonlinear and most of dynamic parameters are uncertainty. Design strong mathematical tools used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance in this controller is the main challenge. Sliding mode methodology is a nonlinear robust controller which can be used in uncertainty nonlinear systems, but pure sliding mode controller has chattering phenomenon and nonlinear equivalent part in uncertain system therefore the first step is focused on eliminate the chattering and in second step controller is improved with regard to uncertainties. Sliding function is one of the most important challenging in artificial sliding mode algorithm which this problem in order to solved by on-line tuning method. This paper focuses on adjusting the sliding surface slope in fuzzy sliding mode controller by sliding mode fuzzy algorithm.
Design Novel Lookup Table Changed Auto Tuning FSMC: Applied to Robot ManipulatorCSCJournals
Refer to this paper, design lookup table changed adaptive fuzzy sliding mode controller with minimum rule base and good response in presence of structure and unstructured uncertainty is presented. However sliding mode controller is one of the robust nonlinear controllers but when this controller is applied to robot manipulator with highly nonlinear and uncertain dynamic function; caused to be challenged in control. Sliding mode controller in presence of uncertainty has two most important drawbacks; chattering and nonlinear equivalent part which proposed method is solved these challenges with look up table change methodology. This method is based on self tuning methodology therefore artificial intelligence (e.g., fuzzy logic method) is played important role to design proposed method. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 s, steady state error = 1e-9 and RMS error=0.00017).
Evolutionary Design of Mathematical tunable FPGA Based MIMO Fuzzy Estimator S...Waqas Tariq
In this research, a Multi Input Multi Output (MIMO) position Field Programmable Gate Array (FPGA)-based fuzzy estimator sliding mode control (SMC) design with the estimation laws derived in Lyapunov sense and application to robotic manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy inference methodology and Lyapunov based method, the controllers output has improved. The main target in this research is analyses and design of the position MIMO artificial Lyapunov FPGA-based controller for robot manipulator in order to solve uncertainty, external disturbance, nonlinear equivalent part, chattering phenomenon, time to market and controller size using FPGA. Robot manipulators are nonlinear, time variant and a number of parameters are uncertain therefore design robust and stable controller based on Lyapunov based is discussed in this research. Studies about classical sliding mode controller (SMC) show that: although this controller has acceptable performance with known dynamic parameters such as stability and robustness but there are two important disadvantages as below: chattering phenomenon and mathematical nonlinear dynamic equivalent controller part. The first challenge; nonlinear dynamic part; is applied by inference estimator method in sliding mode controller in order to solve the nonlinear problems in classical sliding mode controller. And the second challenge; chattering phenomenon; is removed by linear method. Asymptotic stability of the closed loop system is also proved in the sense of Lyapunov. In the last part it can find the implementation of MIMO fuzzy estimator sliding mode controller on FPGA; FPGA-based fuzzy estimator sliding mode controller has many advantages such as high speed, low cost, short time to market and small device size. One of the most important drawbacks is limited capacity of available cells which this research focuses to solve this challenge. FPGA can be used to design a controller in a single chip Integrated Circuit (IC). In this research the SMC is designed using Very High Description Language (VHDL) for implementation on FPGA device (XA3S1600E-Spartan-3E), with minimum chattering.
TORQUE CONTROL OF AC MOTOR WITH FOPID CONTROLLER BASED ON FUZZY NEURAL ALGORITHMijics
Nowadays in the complicated systems, design of proper and implementable controller has a most importance. With respect to ability of fractional order systems in complicated systems identification as a first order fractional system with time delay, usage of fractional order PID has a proper result. From one side flexibility of fractional calculus than integer order has been topics of interest to the researchers. From another side, PMSM motors which are one the AC motor types, has been allocated largely accounted position in industry and used in variety applications. Therefore in this paper torque direct control of PMSM motors with FOPID based on model is proposed. Also fuzzy neural controllers are widely considered. Reason of this is success of fuzzy neural controller in control and identification of uncertain and complicated systems. The proposed method in this paper is combination of FOPID controller with fuzzy neural supervision system which with coefficients setting of this controller, control operation of PMSM will improve. Results of proposed method show the ability of proposed technique in reference signal tracking, elimination of disturbances effects and functional robustness in presence of noise and uncertainty. The results show the error averagely in three condition, nominal form, step disturbance and noise and uncertainly will decrease 11.66% in proposed method (FNFOPID) with Integral Square Error criterion and 7.69% with Integral Absolute Error criterion in comparison to FOPID.
Speed Sensorless Vector Control of Unbalanced Three-Phase Induction Motor wit...IAES-IJPEDS
This paper presents a technique for speed sensorless Rotor Flux Oriented Control (RFOC) of 3-phase Induction Motor (IM) under open-phase fault (unbalanced or faulty IM). The presented RFOC strategy is based on rotational transformation. An adaptive sliding mode control system with an adaptive switching gain is proposed instead of the speed PI controller. Using an adaptive sliding mode control causes the proposed speed sensorless RFOC drive system to become insensitive to uncertainties such as load disturbances and parameter variations. Moreover, with adaptation of the sliding switching gain, calculation of the system uncertainties upper bound is not needed. Finally, simulation results have been presented to confirm the good performance of the proposed method.
Adaptive MIMO Fuzzy Compensate Fuzzy Sliding Mode Algorithm: Applied to Secon...CSCJournals
This research is focused on proposed adaptive fuzzy sliding mode algorithms with the adaptation laws derived in the Lyapunov sense. The stability of the closed-loop system is proved mathematically based on the Lyapunov method. Adaptive MIMO fuzzy compensate fuzzy sliding mode method design a MIMO fuzzy system to compensate for the model uncertainties of the system, and chattering also solved by linear saturation method. Since there is no tuning method to adjust the premise part of fuzzy rules so we presented a scheme to online tune consequence part of fuzzy rules. Classical sliding mode control is robust to control model uncertainties and external disturbances. A sliding mode method with a switching control low guarantees the stability of the certain and/or uncertain system, but the addition of the switching control low introduces chattering into the system. One way to reduce or eliminate chattering is to insert a boundary layer method inside of a boundary layer around the sliding surface. Classical sliding mode control method has difficulty in handling unstructured model uncertainties. One can overcome this problem by combining a sliding mode controller and artificial intelligence (e.g. fuzzy logic). To approximate a time-varying nonlinear dynamic system, a fuzzy system requires a large amount of fuzzy rule base. This large number of fuzzy rules will cause a high computation load. The addition of an adaptive law to a fuzzy sliding mode controller to online tune the parameters of the fuzzy rules in use will ensure a moderate computational load. The adaptive laws in this algorithm are designed based on the Lyapunov stability theorem. Asymptotic stability of the closed loop system is also proved in the sense of Lyapunov.
Novel Method of FOC to Speed Control in Three-Phase IM under Normal and Fault...IJPEDS-IAES
This paper proposes a novel method for speed control of three-phase
induction motor (IM) which can be used for both healthy three-phase IM and
three-phase IM under open-phase fault. The proposed fault-tolerant control
system is derived from conventional field-oriented control (FOC) algorithm
with minor changes on it. The presented drive system is based on using an
appropriate transformation matrix for the stator current variables. The
presented method in this paper can be also used for speed control of singlephase
IMs with two windings. The feasibility of the proposed strategy is
verified by simulation results.
Speed Control of Induction Motor by Using Intelligence TechniquesIJERA Editor
This paper gives the comparative study among various techniques used to control the speed of three phase induction motor. In this paper, indirect vector method is used to control the speed of Induction motor. Firstly Simulink Model is developed by using MATLAB/ Simulink software. PI controller, Fuzzy PI Hybrid controller, Genetic Algorithm (GA) are the techniques involved in control Induction motor and the results are compared. By converting three phase supply currents coming from stator to Flux and Torque components of current the speed responses such as rise time, overshoot, settling time and speed regulation at load have been observed and compared among the techniques. The PI controller parameters defined by an objective function are calculated by using Genetic Algorithms presented good performance compared to Fuzzy PI Hybrid controller which has parameters chosen by the human operator.
Digital Implementation of Fuzzy Logic Controller for Real Time Position Contr...IOSR Journals
Fuzzy Logic Controller (FLC) systems have emerged as one of the most promising areas for
Industrial Applications. The highly growth of fuzzy logic applications led to the need of finding efficient way to
hardware implementation. Field Programmable Gate Array (FPGA) is the most important tool for hardware
implementation due to low consumption of energy, high speed of operation and large capacity of data storage.
In this paper, instead of an introduction to fuzzy logic control methodology, we have demonstrated the
implementation of a FLC through the use of the Very high speed integrated circuits Hardware Description
Language (VHDL) code. FLC is designed for position control of BLDC Motor. VHDL has been used to develop
FLC on FPGA. A Mamdani type FLC structure has been used to obtain the controller output. The controller
algorithm developed synthesized, simulated and implemented on FPGA Spartan 3E board.
Speed Control of Induction Motor using FOC MethodIJERA Editor
An increasing number of applications in high performing electrical drive systems use nowadays, squirrel-cage induction motors. This paper describes a simplified method for the speed control of a three phase AC drive using Proportional-Integral controller. The simulation results show that the step response of the model is very fast, steady and able to work in four quadrants, and robustness and high performance is achieved.
Speed Sensorless Vector Control of Induction Motor Drive with PI and Fuzzy Co...IJPEDS-IAES
This paper directed the speed-sensorless vector control of induction motor drive with PI and fuzzy controllers. Natural observer with fourth order state space model is employed to estimate the speed and rotor fluxes of the induction motor. The formation of the natural observer is similar to and as well as its attribute is identical to the induction motor. Load torque adaptation is provided to estimate the torque and rotor speed is estimated from the load torque, rotor fluxes and stator currents. There is no direct feedback in natural observer and also observer gain matrix is absent. Both the induction motor and the observer are characterized by state space model. Simple fuzzy logic controller and conventional PI controllers are used to control the speed of the induction motor in closed loop. MATLAB simulations are made with PI and fuzzy controllers and the performance of fuzzy controller is better than PI controller in view of torque ripples. The simulation results are obtained for various running conditions to exhibit the suitability of this method for sensorless vector control. Experimental results are provided for natual observer based sensorless vector control with conventional PI controller.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
As the robot manipulators are highly nonlinear, time varying and Multiple Input Multiple Output (MIMO)
systems, one of the most important challenges in the field of robotics is robot manipulators control with
acceptable performance. In this research paper, a simple and computationally efficient Fuzzy Logic
Controller is designed based on the Fuzzy Lyapunov Synthesis (FLS) for the position control of PUMA-560
robot manipulator. The proposed methodology enables the designer to systematically derive the rule base
thereby guarantees the stability of the controller. The methodology is model free and does not require any
information about the system nonlinearities, uncertainties, time varying parameters, etc. The performance
of any fuzzy logic controller (FLC) is greatly dependent on its inference rules. The closed-loop control
performance and stability are enhanced if more rules are added to the rule base of the FLC. However, a
large set of rules requires more on-line computational time and more parameters need to be adjusted.
Here, a Fuzzy Logic Controller is first designed and then the controller based on FLS is designed and
simulated with a minimum rule base. Finally the simulation results of the proposed controller are
compared with that of the normal Fuzzy Logic Controller and PD controlled Computed Torque Controller
(PD-CTC). Results show that the proposed controller outperformed the other controllers.
Design of Model Free Adaptive Fuzzy Computed Torque Controller for a Nonlinea...Waqas Tariq
In this study, a model free adaptive fuzzy computed torque controller (AFCTC) is designed for a two-degree-of freedom robot manipulator to rich the best performance. Computed torque controller is studied because of its high performance. AFCTC has been also included in this study because of its robust character and high performance. Besides, this control method can be applied to non-linear systems easily. Today, robot manipulators are used in unknown and unstructured environment and caused to provide sophisticated systems, therefore strong mathematical tools are used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance (e.g., minimum error, good trajectory, disturbance rejection). The strategies of control robot manipulator are classified into two main groups: classical and non-classical methods, however both classical and non-classical theories have been applied successfully in many applications, but they also have some limitation. One of the most important nonlinear robust controller that can used in uncertainty nonlinear systems, are computed torque controller. This paper is focuses on applied non-classical method in robust classical method to reduce the limitations. Therefore adaptive fuzzy computed torque controller will be presented in this paper.
For Induction motor is a system that works at their speed, nevertheless there are applications at which the speed operations are needed. The control of range of speed of induction motor techniques is available. The robust control is used with induction motor and the performance of the system with the controller will be improved. The mathematical model to the controller, which were coded in MATLAB. The modeling and controller will be shown by the conditions of robustness of be less than one.
Artificial Chattering Free on-line Fuzzy Sliding Mode Algorithm for Uncertain...CSCJournals
In this research, an artificial chattering free adaptive fuzzy sliding mode control design and application to uncertain robotic manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy logic controller and adaptive method, the output has improved. Each method by adding to the previous controller has covered negative points. The main target in this research is design of model free estimator on-line sliding mode fuzzy algorithm for robot manipulator to reach an acceptable performance. Robot manipulators are highly nonlinear, and a number of parameters are uncertain, therefore design model free controller using both analytical and empirical paradigms are the main goal. Although classical sliding mode methodology has acceptable performance with known dynamic parameters such as stability and robustness but there are two important disadvantages as below: chattering phenomenon and mathematical nonlinear dynamic equivalent controller part. To solve the chattering fuzzy logic inference applied instead of dead zone function. To solve the equivalent problems in classical sliding mode controller this paper focuses on applied fuzzy logic method in classical controller. This algorithm works very well in certain environment but in uncertain or various dynamic parameters, it has slight chattering phenomenon. The system performance in sliding mode controller and fuzzy sliding mode controller are sensitive to the sliding function. Therefore, compute the optimum value of sliding function for a system is the next challenge. This problem has solved by adjusting sliding function of the adaptive method continuously in real-time. In this way, the overall system performance has improved with respect to the classical sliding mode controller. This controller solved chattering phenomenon as well as mathematical nonlinear equivalent part by applied fuzzy supervisory method in sliding mode fuzzy controller and tuning the sliding function.
PUMA-560 Robot Manipulator Position Computed Torque Control Methods Using MAT...Waqas Tariq
This paper describes the MATLAB/SIMULINK realization of the PUMA 560 robot manipulator position control methodology. This paper focuses on design, analyzed and implements nonlinear computed torque control (CTC) methods. These simulation models are developed as a part of a software laboratory to support and enhance graduate/undergraduate robotics courses, nonlinear control courses and MATLAB/SIMULINK courses at research and development company (SSP Co.) research center, Shiraz, Iran.
PUMA-560 Robot Manipulator Position Sliding Mode Control Methods Using MATLAB...Waqas Tariq
This paper describes the MATLAB/SIMULINK realization, modeling and implementation of the PUMA 560 robot manipulator. This paper focuses on robot manipulator analysis and implementation and analyzed. This simulation models are developed as a part of a software laboratory to support and enhance graduate robotics courses, and MATLAB/SIMULINK courses at research and development company (SSP Co.) research center, Shiraz, Iran.
Design Error-based Linear Model-free Evaluation Performance Computed Torque C...Waqas Tariq
Design a nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This research focuses on the design, implementation and analysis of a model-free linear error-based tuning computed torque controller for highly nonlinear dynamic second order system, in presence of uncertainties. In order to provide high performance nonlinear methodology, computed torque controller is selected. Pure computed torque controller can be used to control of partly known nonlinear dynamic parameters of nonlinear systems. Conversely, pure computed torque controller is used in many applications; it has an important drawback namely; nonlinear equivalent dynamic formulation in uncertain dynamic parameter. In order to solve the uncertain nonlinear dynamic parameters, implement easily and avoid mathematical model base controller, model-free performance/error-based linear methodology with three inputs and one output is applied to pure computed torque controller. The results demonstrate that the error-based linear tuning computed torque controller is a model-based controllers which works well in certain and uncertain system. Pure computed torque controller has difficulty in handling unstructured model uncertainties. To solve this problem applied linear model-free error -based tuning method to computed torque controller for adjusting the linear inner loop gain (K ). Since the linear inner loop gain (K) is adjusted by linear error-based tuning method, it is linear and continuous. In this research new K is obtained by the previous K multiple gain updating factor (á) which is a coefficient varies between half to two.
The developed control methodology can be used to build more efficient intelligent and precision mechatronic systems. Three degrees of freedom robot arm is controlled by adaptive sliding mode fuzzy algorithm fuzzy sliding mode controller (SMFAFSMC). This plant has 3 revolute joints allowing the corresponding links to move horizontally. Control of robotic manipulator is very important in field of robotic, because robotic manipulators are Multi-Input Multi-Output (MIMO), nonlinear and most of dynamic parameters are uncertainty. Design strong mathematical tools used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance in this controller is the main challenge. Sliding mode methodology is a nonlinear robust controller which can be used in uncertainty nonlinear systems, but pure sliding mode controller has chattering phenomenon and nonlinear equivalent part in uncertain system therefore the first step is focused on eliminate the chattering and in second step controller is improved with regard to uncertainties. Sliding function is one of the most important challenging in artificial sliding mode algorithm which this problem in order to solved by on-line tuning method. This paper focuses on adjusting the sliding surface slope in fuzzy sliding mode controller by sliding mode fuzzy algorithm.
Design Novel Lookup Table Changed Auto Tuning FSMC: Applied to Robot ManipulatorCSCJournals
Refer to this paper, design lookup table changed adaptive fuzzy sliding mode controller with minimum rule base and good response in presence of structure and unstructured uncertainty is presented. However sliding mode controller is one of the robust nonlinear controllers but when this controller is applied to robot manipulator with highly nonlinear and uncertain dynamic function; caused to be challenged in control. Sliding mode controller in presence of uncertainty has two most important drawbacks; chattering and nonlinear equivalent part which proposed method is solved these challenges with look up table change methodology. This method is based on self tuning methodology therefore artificial intelligence (e.g., fuzzy logic method) is played important role to design proposed method. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 s, steady state error = 1e-9 and RMS error=0.00017).
Evolutionary Design of Mathematical tunable FPGA Based MIMO Fuzzy Estimator S...Waqas Tariq
In this research, a Multi Input Multi Output (MIMO) position Field Programmable Gate Array (FPGA)-based fuzzy estimator sliding mode control (SMC) design with the estimation laws derived in Lyapunov sense and application to robotic manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy inference methodology and Lyapunov based method, the controllers output has improved. The main target in this research is analyses and design of the position MIMO artificial Lyapunov FPGA-based controller for robot manipulator in order to solve uncertainty, external disturbance, nonlinear equivalent part, chattering phenomenon, time to market and controller size using FPGA. Robot manipulators are nonlinear, time variant and a number of parameters are uncertain therefore design robust and stable controller based on Lyapunov based is discussed in this research. Studies about classical sliding mode controller (SMC) show that: although this controller has acceptable performance with known dynamic parameters such as stability and robustness but there are two important disadvantages as below: chattering phenomenon and mathematical nonlinear dynamic equivalent controller part. The first challenge; nonlinear dynamic part; is applied by inference estimator method in sliding mode controller in order to solve the nonlinear problems in classical sliding mode controller. And the second challenge; chattering phenomenon; is removed by linear method. Asymptotic stability of the closed loop system is also proved in the sense of Lyapunov. In the last part it can find the implementation of MIMO fuzzy estimator sliding mode controller on FPGA; FPGA-based fuzzy estimator sliding mode controller has many advantages such as high speed, low cost, short time to market and small device size. One of the most important drawbacks is limited capacity of available cells which this research focuses to solve this challenge. FPGA can be used to design a controller in a single chip Integrated Circuit (IC). In this research the SMC is designed using Very High Description Language (VHDL) for implementation on FPGA device (XA3S1600E-Spartan-3E), with minimum chattering.
TORQUE CONTROL OF AC MOTOR WITH FOPID CONTROLLER BASED ON FUZZY NEURAL ALGORITHMijics
Nowadays in the complicated systems, design of proper and implementable controller has a most importance. With respect to ability of fractional order systems in complicated systems identification as a first order fractional system with time delay, usage of fractional order PID has a proper result. From one side flexibility of fractional calculus than integer order has been topics of interest to the researchers. From another side, PMSM motors which are one the AC motor types, has been allocated largely accounted position in industry and used in variety applications. Therefore in this paper torque direct control of PMSM motors with FOPID based on model is proposed. Also fuzzy neural controllers are widely considered. Reason of this is success of fuzzy neural controller in control and identification of uncertain and complicated systems. The proposed method in this paper is combination of FOPID controller with fuzzy neural supervision system which with coefficients setting of this controller, control operation of PMSM will improve. Results of proposed method show the ability of proposed technique in reference signal tracking, elimination of disturbances effects and functional robustness in presence of noise and uncertainty. The results show the error averagely in three condition, nominal form, step disturbance and noise and uncertainly will decrease 11.66% in proposed method (FNFOPID) with Integral Square Error criterion and 7.69% with Integral Absolute Error criterion in comparison to FOPID.
Speed Sensorless Vector Control of Unbalanced Three-Phase Induction Motor wit...IAES-IJPEDS
This paper presents a technique for speed sensorless Rotor Flux Oriented Control (RFOC) of 3-phase Induction Motor (IM) under open-phase fault (unbalanced or faulty IM). The presented RFOC strategy is based on rotational transformation. An adaptive sliding mode control system with an adaptive switching gain is proposed instead of the speed PI controller. Using an adaptive sliding mode control causes the proposed speed sensorless RFOC drive system to become insensitive to uncertainties such as load disturbances and parameter variations. Moreover, with adaptation of the sliding switching gain, calculation of the system uncertainties upper bound is not needed. Finally, simulation results have been presented to confirm the good performance of the proposed method.
Adaptive MIMO Fuzzy Compensate Fuzzy Sliding Mode Algorithm: Applied to Secon...CSCJournals
This research is focused on proposed adaptive fuzzy sliding mode algorithms with the adaptation laws derived in the Lyapunov sense. The stability of the closed-loop system is proved mathematically based on the Lyapunov method. Adaptive MIMO fuzzy compensate fuzzy sliding mode method design a MIMO fuzzy system to compensate for the model uncertainties of the system, and chattering also solved by linear saturation method. Since there is no tuning method to adjust the premise part of fuzzy rules so we presented a scheme to online tune consequence part of fuzzy rules. Classical sliding mode control is robust to control model uncertainties and external disturbances. A sliding mode method with a switching control low guarantees the stability of the certain and/or uncertain system, but the addition of the switching control low introduces chattering into the system. One way to reduce or eliminate chattering is to insert a boundary layer method inside of a boundary layer around the sliding surface. Classical sliding mode control method has difficulty in handling unstructured model uncertainties. One can overcome this problem by combining a sliding mode controller and artificial intelligence (e.g. fuzzy logic). To approximate a time-varying nonlinear dynamic system, a fuzzy system requires a large amount of fuzzy rule base. This large number of fuzzy rules will cause a high computation load. The addition of an adaptive law to a fuzzy sliding mode controller to online tune the parameters of the fuzzy rules in use will ensure a moderate computational load. The adaptive laws in this algorithm are designed based on the Lyapunov stability theorem. Asymptotic stability of the closed loop system is also proved in the sense of Lyapunov.
Novel Method of FOC to Speed Control in Three-Phase IM under Normal and Fault...IJPEDS-IAES
This paper proposes a novel method for speed control of three-phase
induction motor (IM) which can be used for both healthy three-phase IM and
three-phase IM under open-phase fault. The proposed fault-tolerant control
system is derived from conventional field-oriented control (FOC) algorithm
with minor changes on it. The presented drive system is based on using an
appropriate transformation matrix for the stator current variables. The
presented method in this paper can be also used for speed control of singlephase
IMs with two windings. The feasibility of the proposed strategy is
verified by simulation results.
Speed Control of Induction Motor by Using Intelligence TechniquesIJERA Editor
This paper gives the comparative study among various techniques used to control the speed of three phase induction motor. In this paper, indirect vector method is used to control the speed of Induction motor. Firstly Simulink Model is developed by using MATLAB/ Simulink software. PI controller, Fuzzy PI Hybrid controller, Genetic Algorithm (GA) are the techniques involved in control Induction motor and the results are compared. By converting three phase supply currents coming from stator to Flux and Torque components of current the speed responses such as rise time, overshoot, settling time and speed regulation at load have been observed and compared among the techniques. The PI controller parameters defined by an objective function are calculated by using Genetic Algorithms presented good performance compared to Fuzzy PI Hybrid controller which has parameters chosen by the human operator.
Digital Implementation of Fuzzy Logic Controller for Real Time Position Contr...IOSR Journals
Fuzzy Logic Controller (FLC) systems have emerged as one of the most promising areas for
Industrial Applications. The highly growth of fuzzy logic applications led to the need of finding efficient way to
hardware implementation. Field Programmable Gate Array (FPGA) is the most important tool for hardware
implementation due to low consumption of energy, high speed of operation and large capacity of data storage.
In this paper, instead of an introduction to fuzzy logic control methodology, we have demonstrated the
implementation of a FLC through the use of the Very high speed integrated circuits Hardware Description
Language (VHDL) code. FLC is designed for position control of BLDC Motor. VHDL has been used to develop
FLC on FPGA. A Mamdani type FLC structure has been used to obtain the controller output. The controller
algorithm developed synthesized, simulated and implemented on FPGA Spartan 3E board.
Speed Control of Induction Motor using FOC MethodIJERA Editor
An increasing number of applications in high performing electrical drive systems use nowadays, squirrel-cage induction motors. This paper describes a simplified method for the speed control of a three phase AC drive using Proportional-Integral controller. The simulation results show that the step response of the model is very fast, steady and able to work in four quadrants, and robustness and high performance is achieved.
Speed Sensorless Vector Control of Induction Motor Drive with PI and Fuzzy Co...IJPEDS-IAES
This paper directed the speed-sensorless vector control of induction motor drive with PI and fuzzy controllers. Natural observer with fourth order state space model is employed to estimate the speed and rotor fluxes of the induction motor. The formation of the natural observer is similar to and as well as its attribute is identical to the induction motor. Load torque adaptation is provided to estimate the torque and rotor speed is estimated from the load torque, rotor fluxes and stator currents. There is no direct feedback in natural observer and also observer gain matrix is absent. Both the induction motor and the observer are characterized by state space model. Simple fuzzy logic controller and conventional PI controllers are used to control the speed of the induction motor in closed loop. MATLAB simulations are made with PI and fuzzy controllers and the performance of fuzzy controller is better than PI controller in view of torque ripples. The simulation results are obtained for various running conditions to exhibit the suitability of this method for sensorless vector control. Experimental results are provided for natual observer based sensorless vector control with conventional PI controller.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
As the robot manipulators are highly nonlinear, time varying and Multiple Input Multiple Output (MIMO)
systems, one of the most important challenges in the field of robotics is robot manipulators control with
acceptable performance. In this research paper, a simple and computationally efficient Fuzzy Logic
Controller is designed based on the Fuzzy Lyapunov Synthesis (FLS) for the position control of PUMA-560
robot manipulator. The proposed methodology enables the designer to systematically derive the rule base
thereby guarantees the stability of the controller. The methodology is model free and does not require any
information about the system nonlinearities, uncertainties, time varying parameters, etc. The performance
of any fuzzy logic controller (FLC) is greatly dependent on its inference rules. The closed-loop control
performance and stability are enhanced if more rules are added to the rule base of the FLC. However, a
large set of rules requires more on-line computational time and more parameters need to be adjusted.
Here, a Fuzzy Logic Controller is first designed and then the controller based on FLS is designed and
simulated with a minimum rule base. Finally the simulation results of the proposed controller are
compared with that of the normal Fuzzy Logic Controller and PD controlled Computed Torque Controller
(PD-CTC). Results show that the proposed controller outperformed the other controllers.
Design of Model Free Adaptive Fuzzy Computed Torque Controller for a Nonlinea...Waqas Tariq
In this study, a model free adaptive fuzzy computed torque controller (AFCTC) is designed for a two-degree-of freedom robot manipulator to rich the best performance. Computed torque controller is studied because of its high performance. AFCTC has been also included in this study because of its robust character and high performance. Besides, this control method can be applied to non-linear systems easily. Today, robot manipulators are used in unknown and unstructured environment and caused to provide sophisticated systems, therefore strong mathematical tools are used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance (e.g., minimum error, good trajectory, disturbance rejection). The strategies of control robot manipulator are classified into two main groups: classical and non-classical methods, however both classical and non-classical theories have been applied successfully in many applications, but they also have some limitation. One of the most important nonlinear robust controller that can used in uncertainty nonlinear systems, are computed torque controller. This paper is focuses on applied non-classical method in robust classical method to reduce the limitations. Therefore adaptive fuzzy computed torque controller will be presented in this paper.
For Induction motor is a system that works at their speed, nevertheless there are applications at which the speed operations are needed. The control of range of speed of induction motor techniques is available. The robust control is used with induction motor and the performance of the system with the controller will be improved. The mathematical model to the controller, which were coded in MATLAB. The modeling and controller will be shown by the conditions of robustness of be less than one.
Artificial Chattering Free on-line Fuzzy Sliding Mode Algorithm for Uncertain...CSCJournals
In this research, an artificial chattering free adaptive fuzzy sliding mode control design and application to uncertain robotic manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy logic controller and adaptive method, the output has improved. Each method by adding to the previous controller has covered negative points. The main target in this research is design of model free estimator on-line sliding mode fuzzy algorithm for robot manipulator to reach an acceptable performance. Robot manipulators are highly nonlinear, and a number of parameters are uncertain, therefore design model free controller using both analytical and empirical paradigms are the main goal. Although classical sliding mode methodology has acceptable performance with known dynamic parameters such as stability and robustness but there are two important disadvantages as below: chattering phenomenon and mathematical nonlinear dynamic equivalent controller part. To solve the chattering fuzzy logic inference applied instead of dead zone function. To solve the equivalent problems in classical sliding mode controller this paper focuses on applied fuzzy logic method in classical controller. This algorithm works very well in certain environment but in uncertain or various dynamic parameters, it has slight chattering phenomenon. The system performance in sliding mode controller and fuzzy sliding mode controller are sensitive to the sliding function. Therefore, compute the optimum value of sliding function for a system is the next challenge. This problem has solved by adjusting sliding function of the adaptive method continuously in real-time. In this way, the overall system performance has improved with respect to the classical sliding mode controller. This controller solved chattering phenomenon as well as mathematical nonlinear equivalent part by applied fuzzy supervisory method in sliding mode fuzzy controller and tuning the sliding function.
PUMA-560 Robot Manipulator Position Computed Torque Control Methods Using MAT...Waqas Tariq
This paper describes the MATLAB/SIMULINK realization of the PUMA 560 robot manipulator position control methodology. This paper focuses on design, analyzed and implements nonlinear computed torque control (CTC) methods. These simulation models are developed as a part of a software laboratory to support and enhance graduate/undergraduate robotics courses, nonlinear control courses and MATLAB/SIMULINK courses at research and development company (SSP Co.) research center, Shiraz, Iran.
PUMA-560 Robot Manipulator Position Sliding Mode Control Methods Using MATLAB...Waqas Tariq
This paper describes the MATLAB/SIMULINK realization, modeling and implementation of the PUMA 560 robot manipulator. This paper focuses on robot manipulator analysis and implementation and analyzed. This simulation models are developed as a part of a software laboratory to support and enhance graduate robotics courses, and MATLAB/SIMULINK courses at research and development company (SSP Co.) research center, Shiraz, Iran.
Evolutionary Design of Backstepping Artificial Sliding Mode Based Position Al...CSCJournals
This paper expands a fuzzy sliding mode based position controller whose sliding function is on-line tuned by backstepping methodology. The main goal is to guarantee acceptable position trajectories tracking between the robot manipulator end-effector and the input desired position. The fuzzy controller in proposed fuzzy sliding mode controller is based on Mamdani’s fuzzy inference system (FIS) and it has one input and one output. The input represents the function between sliding function, error and the rate of error. The second input is the angle formed by the straight line defined with the orientation of the robot, and the straight line that connects the robot with the reference cart. The outputs represent angular position, velocity and acceleration commands, respectively. The backstepping methodology is on-line tune the sliding function based on self tuning methodology. The performance of the backstepping on-line tune fuzzy sliding mode controller (TBsFSMC) is validated through comparison with previously developed robot manipulator position controller based on adaptive fuzzy sliding mode control theory (AFSMC). Simulation results signify good performance of position tracking in presence of uncertainty and external disturbance.
Sliding Mode Methodology Vs. Computed Torque Methodology Using MATLAB/SIMULIN...CSCJournals
Design a nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This paper focuses on the design, implementation and analysis of a chattering free sliding mode controller for highly nonlinear dynamic PUMA robot manipulator and compare to computed torque controller, in presence of uncertainties. In order to provide high performance nonlinear methodology, sliding mode controller and computed torque controller are selected. Pure sliding mode controller and computed torque controller can be used to control of partly known nonlinear dynamic parameters of robot manipulator. Conversely, pure sliding mode controller is used in many applications; it has an important drawback namely; chattering phenomenon which it can causes some problems such as saturation and heat the mechanical parts of robot manipulators or drivers. In order to reduce the chattering this research is used the linear saturation function boundary layer method instead of switching function method in pure sliding mode controller. These simulation models are developed as a part of a software laboratory to support and enhance graduate/undergraduate robotics courses, nonlinear control courses and MATLAB/SIMULINK courses at research and development company (SSP Co.) research center, Shiraz, Iran.
Design and Implementation of Sliding Mode Algorithm: Applied to Robot Manipul...Waqas Tariq
Refer to the research, review of sliding mode controller is introduced and application to robot manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy logic controller and adaptive method, the output in most of research have improved. Each method by adding to the previous algorithm has covered negative points. Obviously robot manipulator is nonlinear, and a number of parameters are uncertain, this research focuses on comparison between sliding mode algorithm which analyzed by many researcher. Sliding mode controller (SMC) is one of the nonlinear robust controllers which it can be used in uncertainty nonlinear dynamic systems. This nonlinear controller has two challenges namely nonlinear dynamic equivalent part and chattering phenomenon. A review of sliding mode controller for robot manipulator will be investigated in this research.
Novel Artificial Control of Nonlinear Uncertain System: Design a Novel Modifi...Waqas Tariq
This research is focused on novel particle swarm optimization (PSO) SISO Lyapunov based fuzzy estimator sliding mode algorithms derived in the Lyapunov sense. The stability of the closed-loop system is proved mathematically based on the Lyapunov method. PSO SISO fuzzy compensate sliding mode method design a SISO fuzzy system to compensate for the dynamic model uncertainties of the nonlinear dynamic system and chattering also solved by nonlinear fuzzy saturation like method. Adjust the sliding function is played important role to reduce the chattering phenomenon and also design acceptable estimator applied to nonlinear classical controller so PSO method is used to off-line tuning. Classical sliding mode control is robust to control model uncertainties and external disturbances. A sliding mode method with a switching control low guarantees the stability of the certain and/or uncertain system, but the addition of the switching control low introduces chattering into the system. One way to reduce or eliminate chattering is to insert a nonlinear (fuzzy) boundary like layer method inside of a boundary layer around the sliding surface. Classical sliding mode control method has difficulty in handling unstructured model uncertainties. One can overcome this problem by applied fuzzy inference system into sliding mode algorithm to design and estimate model-free nonlinear dynamic equivalent part. To approximate a time-varying nonlinear dynamic system, a fuzzy system requires a large amount of fuzzy rule base. This large number of fuzzy rules will cause a high computation load. The addition of PSO method to a fuzzy sliding mode controller to tune the parameters of the fuzzy rules in use will ensure a moderate computational load. The PSO method in this algorithm is designed based on the PSO stability theorem. Asymptotic stability of the closed loop system is also proved in the sense of Lyapunov.
Position Control of Robot Manipulator: Design a Novel SISO Adaptive Sliding M...Waqas Tariq
This research focuses on design Single Input Single Output (SISO) adaptive sliding mode fuzzy PD fuzzy sliding mode algorithm with estimates the equivalent part derived in the Lyapunov sense. The stability of the closed-loop system is proved mathematically based on the Lyapunov method. Proposed method introduces a SISO fuzzy system to compensate for the model uncertainties of the system and eliminate the chattering by linear boundary layer method. This algorithm is used a SISO fuzzy system to alleviate chattering and to estimate the control gain in the control law and presented a scheme to online tune of sliding function. To attenuate the chattering phenomenon this method developed a linear boundary layer and the parameter of the sliding function is online tuned by adaptation laws. This algorithm will be analyzed and evaluated on robotic manipulators and design adaption laws of adaptive algorithms after that writing Lyapunov function candidates and prove the asymptotic convergence of the closed-loop system using Lyapunov stability theorem mathematically. Compare and evaluate proposed method and sliding mode algorithms under disturbance. In regards to the former, we will be looking at the availability of online tuning methodology and the number of fuzzy if-then rules inherent to the fuzzy system being used and the corresponding computational load. Our analysis of the results will be limited to tracking accuracy and chattering.
Robust Fault Detection and Isolation using Bond Graph for an Active-Passive V...CSCJournals
A robot is a complex machine, comprising mechanism, actuators, sensors, and electrical system. It is, therefore, hard to guarantee that all the components can always function normally. If one component fails, the robot might harm humans. In order to develop the active-passive variable serial elastic actuator (APVSEA) [1] that can detect the occurrence of any component fault, this paper uses bond graph to design a robust fault detection and isolation (RFDI) system. When the robot components malfunction, the RFDI system will execute suitable isolation strategies to guarantee human safety and use zero-gravity control (ZGC) to simultaneously compensate for the torque caused by gravity. Thus, the user can consistently interact with the robot easily and safely. From the experimental results, the RFDI system can filter out uncertain parameters and identify the failed component. In addition, the zero-gravity control can lessen potentially physical damage to humans.
This paper expands a sliding mode fuzzy controller which sliding surface gain is on-line tuned by minimum fuzzy inference algorithm. The main goal is to guarantee acceptable trajectories tracking between the second order nonlinear system (robot manipulator) actual and the desired trajectory. The fuzzy controller in proposed sliding mode fuzzy controller is based on Mamdani’s fuzzy inference system (FIS) and it has one input and one output. The input represents the function between sliding function, error and the rate of error. The outputs represent torque, respectively. The fuzzy inference system methodology is on-line tune the sliding surface gain based on error-based fuzzy tuning methodology. Pure sliding mode fuzzy controller has difficulty in handling unstructured model uncertainties. To solve this problem applied fuzzy-based tuning method to sliding mode fuzzy controller for adjusting the sliding surface gain (ë ). Since the sliding surface gain (ë) is adjusted by fuzzy-based tuning method, it is nonlinear and continuous. Fuzzy-based tuning sliding mode fuzzy controller is stable model-free controller which eliminates the chattering phenomenon without to use the boundary layer saturation function. Lyapunov stability is proved in fuzzy-based tuning sliding mode fuzzy controller based on switching (sign) function. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=0%, rise time=0.8 second, steady state error = 1e-9 and RMS error=1.8e-12).
Comparison of different controllers for the improvement of Dynamic response o...IJERA Editor
As the technology is fast changing, there is more and more use of machine intelligence in modern motor controllers. These controllers are employed in advanced electric motor drives in particular, the present day Induction motor drives. These systems emulate the human logic. This is particularly useful when the application has poorly defined mathematical model. In this present paper the analysis of fuzzy logic as the artificial intelligence is used. The comparative study of Fuzzy PI, Fuzzy MRAC is made. There is always a compromise of the cost and complexity. So this paper presents a new approach and its dynamic response in comparison to the Fuzzy PI and Fuzzy MRAC. The proposed controller is Fuzzy PI with scaling factors. This approach is validated with the Speed, torque responses of Indirect vector controlled Induction motor (IVCIM) drive.
Digital Implementation of Fuzzy Logic Controller for Real Time Position Contr...IOSR Journals
Abstract: Fuzzy Logic Controller (FLC) systems have emerged as one of the most promising areas for Industrial Applications. The highly growth of fuzzy logic applications led to the need of finding efficient way to hardware implementation. Field Programmable Gate Array (FPGA) is the most important tool for hardware implementation due to low consumption of energy, high speed of operation and large capacity of data storage. In this paper, instead of an introduction to fuzzy logic control methodology, we have demonstrated the implementation of a FLC through the use of the Very high speed integrated circuits Hardware Description Language (VHDL) code. FLC is designed for position control of BLDC Motor. VHDL has been used to develop FLC on FPGA. A Mamdani type FLC structure has been used to obtain the controller output. The controller algorithm developed synthesized, simulated and implemented on FPGA Spartan 3E board. Keywords – BLDC Motor, FLC, Hardware Implementation, Spartan3 FPGA, VHDL
On line Tuning Premise and Consequence FIS: Design Fuzzy Adaptive Fuzzy Slidi...Waqas Tariq
One of the most active research areas in the field of robotics is robot manipulators control, because these systems are multi-input multi-output (MIMO), nonlinear, and uncertainty. At present, robot manipulators is used in unknown and unstructured situation and caused to provide complicated systems, consequently strong mathematical tools are used in new control methodologies to design nonlinear robust controller with satisfactory performance (e.g., minimum error, good trajectory, disturbance rejection). Robotic systems controlling is vital due to the wide range of application. Obviously stability and robustness are the most minimum requirements in control systems; even though the proof of stability and robustness is more important especially in the case of nonlinear systems. One of the best nonlinear robust controllers which can be used in uncertainty nonlinear systems is sliding mode controller (SMC). Chattering phenomenon is the most important challenge in this controller. Most of nonlinear controllers need real time mobility operation; one of the most important devices which can be used to solve this challenge is Field Programmable Gate Array (FPGA). FPGA can be used to design a controller in a single chip Integrated Circuit (IC). In this research the SMC is designed using VHDL language for implementation on FPGA device (XA3S1600E-Spartan-3E), with minimum chattering and high processing speed (63.29 MHz).
Intelligent swarm algorithms for optimizing nonlinear sliding mode controller...IJECEIAES
This work introduces an accurate and fast approach for optimizing the parameters of robot manipulator controller. The approach of sliding mode control (SMC) was proposed as it documented an effective tool for designing robust controllers for complex high-order linear and nonlinear dynamic systems operating under uncertain conditions. In this work Intelligent particle swarm optimization (PSO) and social spider optimization (SSO) were used for obtaining the best values for the parameters of sliding mode control (SMC) to achieve consistency, stability and robustness. Additional design of integral sliding mode control (ISMC) was implemented to the dynamic system to achieve the high control theory of sliding mode controller. For designing particle swarm optimizer (PSO) and social spider optimization (SSO) processes, mean square error performances index was considered. The effectiveness of the proposed system was tested with six degrees of freedom robot manipulator by using (PUMA) robot. The iteration of SSO and PSO algorithms with mean square error and objective function were obtained, with best fitness for (SSO =4.4876 푒 −6 and (PSO)=3.4948 푒 −4 .
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
A High Gain Observer Based Sensorless Nonlinear Control of Induction MachineIJPEDS-IAES
In this paper a sensorless Backstepping control scheme for rotor speed and flux control of induction motor drive is proposed. The most interesting feature of this technique is to deal with non-linearity of high-order system by using a virtual control variable to render the system simple. In this technique, the control outputs can be derived step by step through appropriate Lyapunov functions. A high gain observer is performed to estimate non available rotor speed and flux measurements to design the full control scheme of the considered induction motor drive. Simulation results are presented to validate the effectiveness of the proposed sensorless Backstepping control of the considered induction motor.
Fractional order PID for tracking control of a parallel robotic manipulator t...ISA Interchange
This paper presents the tracking control for a robotic manipulator type delta employing fractional order PID controllers with computed torque control strategy. It is contrasted with an integer order PID controller with computed torque control strategy. The mechanical structure, kinematics and dynamic models of the delta robot are descripted. A SOLIDWORKS/MSC-ADAMS/MATLAB co-simulation model of the delta robot is built and employed for the stages of identification, design, and validation of control strategies. Identification of the dynamic model of the robot is performed using the least squares algorithm. A linearized model of the robotic system is obtained employing the computed torque control strategy resulting in a decoupled double integrating system. From the linearized model of the delta robot, fractional order PID and integer order PID controllers are designed, analyzing the dynamical behavior for many evaluation trajectories. Controllers robustness is evaluated against external disturbances employing performance indexes for the joint and spatial error, applied torque in the joints and trajectory tracking. Results show that fractional order PID with the computed torque control strategy has a robust performance and active disturbance rejection when it is applied to parallel robotic manipulators on tracking tasks.
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This paper presents the design of a fuzzy tracking controller for balancing and velocity control of a Two-Wheeled Inverted Pendulum (TWIP) mobile robot based on its Takagi-Sugino (T-S) fuzzy model, fuzzy Lyapunov function and non-parallel distributed compensation (non-PDC) control law. The T-S fuzzy model of the TWIP mobile robot was developed from its nonlinear dynamical equations of motion. Stabilization conditions in a form of linear matrix inequalities (LMIs) were derived based on the T-S fuzzy model of the TWIP mobile robot, a fuzzy Lyapunov function and a non-PDC control law. Based on the derived stabilization conditions and the T-S fuzzy model of the TWIP mobile robot, a state feedback velocity tracking controller was then proposed for the TWIP mobile robot. The balancing and velocity tracking performance of the proposed controller was investigated via simulations. The simulation result shows the effectiveness of the proposed control scheme.
Comparative Analysis for NN-Based Adaptive Back-stepping Controller and Back-...IJERA Editor
This work primarily addresses the design and implementation of a neural network based controller for the trajectory tracking of a differential drive mobile robot. The proposed control algorithm is an NN-based adaptive controller which tunes the gains of the back-stepping controller online according to the robot reference trajectory and its initial posture. In this method, a neural network is needed to learn the characteristics of the plant dynamics and make use of it to determine the future inputs that will minimize error performance index so as to compensate the back-stepping controller gains. The advantages and disadvantages of theproposed control algorithms will be discussed in each section with illustrations.Comprehensive system modeling including robot kinematics and dynamics modeling has been done. The dynamic modeling is done using Newtonian and Lagrangian methodologies for nonholonomic systems and the results are compared to verify the accuracy of each method. Simulation of the robot model and different controllers has been done using Matlab and Matlab Simulink.
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1. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 13
Design Adaptive Artificial Inverse Dynamic Controller: Design
Sliding Mode Fuzzy Adaptive New Inverse Dynamic Fuzzy
Controller
Farzin Piltan SSP.ROBOTIC@yahoo.com
Industrial Electrical and Electronic
Engineering SanatkadeheSabze
Pasargad. CO (S.S.P. Co), NO:16
,PO.Code 71347-66773, Fourth floor
Dena Apr , Seven Tir Ave , Shiraz , Iran
Mohammad A. Bairami SSP.ROBOTIC@yahoo.com
Industrial Electrical and Electronic
Engineering SanatkadeheSabze
Pasargad. CO (S.S.P. Co), NO:16
,PO.Code 71347-66773, Fourth floor
Dena Apr , Seven Tir Ave , Shiraz , Iran
Farid Aghayari SSP.ROBOTIC@yahoo.com
Industrial Electrical and Electronic
Engineering SanatkadeheSabze
Pasargad. CO (S.S.P. Co), NO:16
,PO.Code 71347-66773, Fourth floor
Dena Apr , Seven Tir Ave , Shiraz , Iran
Sadeq Allahdadi SSP.ROBOTIC@yahoo.com
Industrial Electrical and Electronic
Engineering SanatkadeheSabze
Pasargad. CO (S.S.P. Co), NO:16
,PO.Code 71347-66773, Fourth floor
Dena Apr , Seven Tir Ave , Shiraz , Iran
Abstract
In this research, a model free sliding mode fuzzy adaptive inverse dynamic fuzzy controller
(SMFIDFC) is designed for a robot manipulator to rich the best performance. Inverse dynamic
controller is considered because of its high performance in certain system. Fuzzy methodology
has been included in inverse dynamic to keep away from design nonlinear controller based on
dynamic model. Sliding mode fuzzy adaptive methodology is applied to model free controller to
have better result in presence of structure and unstructured uncertainties. Besides, this control
method can be applied to non-linear systems easily. Today, strong mathematical tools are used
in new control methodologies to design adaptive nonlinear controller with satisfactory output
results (e.g., minimum error, good trajectory, disturbance rejection).
Keywords: Inverse Dynamic Controller, Fuzzy Logic Methodology, Inverse Dynamic Fuzzy
Controller, Adaptive Methodology, Sliding Mode Fuzzy Adaptive Inverse Dynamic Fuzzy
Methodology.
1. INTRODUCTION, BACKGROUND AND MOTIVATION
Robot manipulators have many applications in aerospace, manufacturing, automotive, medicine
and other industries. Robot manipulators consist of three main parts: mechanical, electrical, and
control. In the mechanical point of view, robot manipulators are collection of serial or parallel links
which have connected by revolute and/or prismatic joints between base and end-effector frame. A
2. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 14
serial link robot is a sequence of joints and links which begins with a base frame and ends with an
end-effector. This type of robot manipulators, comparing with the load capacitance is more
weightily because each link must be supported the weights of all next links and actuators
between the present link and end-effector[6]. Serial robot manipulators have been used in
automotive industry, medical application, and also in research laboratories. In 1978 the serial link
PUMA (Programmable Universal Machine for Assembly) was introduced and it was quickly used
in research laboratories and industries. Dynamic equation is the study of motion with regard to
forces. Dynamic modeling is vital for control, mechanical design, and simulation. It is used to
describe dynamic parameters and also to describe the relationship between displacement,
velocity and acceleration to force acting on robot manipulator [1-2].
Inverse dynamics control (IDC) is based on cancelling decoupling and nonlinear terms of
dynamics of each link. Inverse dynamics control is a powerful nonlinear controller which it widely
used in control robot manipulator. It is based on Feed-back linearization and computes the
required arm torques using the nonlinear feedback control law. This controller works very well
when all dynamic and physical parameters are known but when the robot manipulator has
variation in dynamic parameters, the controller has no acceptable performance[14]. In practice,
most of physical systems (e.g., robot manipulators) parameters are unknown or time variant,
therefore, Inverse dynamics fuzzy control used to compensate dynamic equation of robot
manipulator[1-2]. Research on Inverse dynamics control is significantly growing on robot
manipulator application which has been reported in [1-2, 4, 7-8, 9, 18, 29]. Vivas and Mosquera
[7]have proposed a predictive functional controller and compare to computed torque controller for
tracking response in uncertain environment. However both controllers have been used in Feed-
back linearization, but predictive strategy gives better result as a performance. An Inverse
dynamics control with non parametric regression models have been presented for a robot arm[7].
This controller also has been problem in uncertain dynamic models. Based on [1-2]and [7-9]
Inverse dynamics control is a significant nonlinear controller to certain systems which it is based
on feedback linearization and computes the required arm torques using the nonlinear feedback
control law. When all dynamic and physical parameters are known the controller works
fantastically; practically a large amount of systems have uncertainties and sliding mode controller
decrease this kind of challenge. Piltan et al. [21] have proposed a simple adaptive fuzzy gain
scheduling for robot manipulator. An independent joint position and stiffness adaptive control
computed torque control has been presented for a robot arm [4]. Soltani and Piltan [46] have
addressed the problem of output feedback tracking control of a robot arm which by computed
torque like controller.
Application of fuzzy logic to automatic control was first reported in [10], where, based on Zadeh's
proposition, Mamdani buit a controller for a steam engine and boiler combination by synthesizing
a set of linguistic expressions in the form of IF-THEN rules as follows: IF (system state) THEN
(control action), which will be referred to as "Mamdani controller' hereafter. In Mamdani's
controller the knowledge of the system state (the IF part) and the set of actions (the THEN part)
are obtained from the experienced human operators [11]. Fuzzy control has gradually been
recognized as the most significant and fruitful application for fuzzy logic. In the past three
decades, more diversified application domains for fuzzy logic controllers have been created,
which range from water cleaning process, home appliances such as air conditioning systems and
online recognition of handwritten symbols [10-15, 20, 36].
Many dynamic systems to be controlled have unknown or varying uncertain parameters. For
instance, robot manipulators may carry large objects with unknown inertial parameters. Generally,
the basic objective of adaptive control is to maintain performance of the closed-loop system in the
presence of uncertainty (e.g., variation in parameters of a robot manipulator). The above
objective can be achieved by estimating the uncertain parameters (or equivalently, the
corresponding controller parameters) on-line, and based on the measured system signals. The
estimated parameters are used in the computation of the control input. An adaptive system can
thus be regarded as a control system with on-line parameter estimation [3, 16-29]. In
conventional nonlinear adaptive controllers, the controller attempts to learn the uncertain
3. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 15
parameters of particular structured dynamics, and can achieve fine control and compensate for
the structure uncertainties and bounded disturbances. On the other hand, adaptive control
techniques are restricted to the parameterization of known functional dependency but of unknown
Constance. Consequently, these factors affect the existing nonlinear adaptive controllers in cases
with a poorly known dynamic model or when the fast real-time control is required. Adaptive
control methodologies and their applications to the robot manipulators have widely been studied
and discussed in the following references [4-5, 16-45].
In this research we will highlight the SISO sliding mode fuzzy adaptive algorithm to on line tuning
inverse dynamic fuzzy controller with estimates the nonlinear dynamic part derived in the
Lyapunov sense. This algorithm will be analyzed and evaluated on robotic manipulators. Section
2, is served as a problem statements, objectives, robot manipulator dynamics and introduction to
the classical inverse dynamic control and its application to robot manipulator. Part 3, introduces
and describes the methodology algorithms, introduced sliding mode controller to design adaptive
part and proves Lyapunov stability. Section 4 presents the simulation results of this algorithm
applied to a 3 degree-of-freedom robot manipulator and the final section is describe the
conclusion.
2. ROBOT MANIPULATOR DYNAMICS, OBJECTIVES, PROBLEM
STATEMENTS and FEEDBACK LINEARIZATION FORMULATION
Robot Manipulator Dynamic Formulation: The equation of an n-DOF robot manipulator
governed by the following equation [1, 3, 16-28, 30, 3840]:
(1)
Where τ is actuation torque, M (q) is a symmetric and positive define inertia matrix, is the
vector of nonlinearity term. This robot manipulator dynamic equation can also be written in a
following form:
(2)
Where B(q) is the matrix of coriolios torques, C(q) is the matrix of centrifugal torques, and G(q) is
the vector of gravity force. The dynamic terms in equation (2) are only manipulator position. This is
a decoupled system with simple second order linear differential dynamics. In other words, the
component influences, with a double integrator relationship, only the joint variable ,
independently of the motion of the other joints. Therefore, the angular acceleration is found as to
be [3, 16-28]:
(3)
Inverse Dynamic Control: This technique is very attractive from a control point of view. The
central idea of inverse dynamic controller (IDC) is feedback linearization so, originally this
algorithm is called inverse dynamic controller. It has assumed that the desired motion trajectory
for the manipulator , as determined, by a path planner. Defines the tracking error as [4-9, 18,
21, 31]:
(4)
Where e(t) is error of the plant, is desired input variable, that in our system is desired
displacement, is actual displacement. If an alternative linear state-space equation in the
form can be defined as
(5)
With and this is known as the Brunousky canonical form. By
equation (4) and (5) the Brunousky canonical form can be written in terms of the state
as [1]:
(6)
4. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 16
With
(7)
Then compute the required arm torques using inverse of equation (7), is;
(8)
This is a nonlinear feedback control law that guarantees tracking of desired trajectory. Selecting
proportional-plus-derivative (PD) feedback for U(t) results in the PD-computed torque controller
[4, 6-9];
(9)
and the resulting linear error dynamics are
(10)
According to the linear system theory, convergence of the tracking error to zero is guaranteed [6].
Where and are the controller gains. The result schemes is shown in Figure 1, in which two
feedback loops, namely, inner loop and outer loop, which an inner loop is a compensate loop and
an outer loop is a tracking error loop. However, mostly parameter is all unknown. So the
control cannot be implementation because non linear parameters cannot be determined. In the
following section computed torque like controller will be introduced to overcome the problems.
FIGURE 1: Block diagram of PD-inverse dynamic controller (PD-IDC)
The application of proportional-plus-derivative (PD) IDC to control of robot manipulator
introduced in this part. PUMA 560 robot manipulator is a nonlinear and uncertain system which
needs to have powerful nonlinear robust controller such as inverse dynamic controller. Suppose
that in (9) the nonlinearity term defined by the following term
(11)
5. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 17
Therefore the equation of PD-IDC for control of PUMA 560 robot manipulator is written as the
equation of (12);
(12)
The controller based on a formulation (12) is related to robot dynamics therefore it has problems
in uncertain conditions.
Problem Statement: inverse dynamic controller is used in wide range areas such as in robotics,
in control process, in aerospace applications and in power converters because it has an
acceptable control performance and solve some main challenging topics in control such as
resistivity to the external disturbance. Even though, this controller is used in wide range areas
but, pure inverse dynamic controller has the disadvantage that the main potential difficulty
encountered in implementation of the inverse dynamic control methodology described above is
that the dynamic model of the robot manipulator to be controlled is often not known accuratly.
Pure fuzzy logic controller (FLC) works in many areas, but it cannot guarantee the basic
requirement of stability and acceptable performance[8]. Although both inverse dynamic controller
and fuzzy logic controller have been applied successfully in many applications but they also have
some limitations. Proposed method focuses on substitution fuzzy logic system applied to main
controller to compensate the uncertainty in nonlinear dynamic equation to implement easily and
avoid mathematical model base controller. To reduce the effect of uncertainty in proposed
method, sliding mode adaptive method is applied in feedback linearization fuzzy controller in
robot manipulator.
Objectives: The main goal in this original paper is to design a new adaptive position controller for
robot manipulator with acceptable performances (e.g., trajectory performance, torque
performance, disturbance rejection, steady state error and RMS error). Robot manipulator has
nonlinear and uncertain dynamic parameters consequently; following objectives have been
pursuit in the mentioned study.
• To design and implement a position inverse dynamic fuzzy controller in order to solve the
uncertainty in nonlinear parameters problems in the pure inverse dynamic control.
• To develop a position sliding mode fuzzy adaptive inverse dynamic fuzzy controller in
order to solve the disturbance rejection.
6. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 18
3. METHODOLOGY: DESIGN A NOVEL SLIDING MODE FUZZY
ADAPTIVE INVERSE DYNAMIC FUZZY ESTIMATION CONTROLLER
First Step, Design Inverse Dynamic Fuzzy Controller: In recent years, artificial intelligence
theory has been used in robotic systems. Neural network, fuzzy logic, and neuro-fuzzy are
combined with nonlinear methods and used in nonlinear, time variant, and uncertainty plant (e.g.,
robot manipulator). This controller can be used to control of nonlinear, uncertain, and noisy
systems. This method is free of some model-based techniques that used in classical controllers.
The main reasons to use fuzzy logic technology are able to give approximate recommended
solution for unclear and complicated systems to easy understanding and flexible. Fuzzy logic
provides a method which is able to model a controller for nonlinear plant with a set of IF-THEN
rules, or it can identify the control actions and describe them by using fuzzy rules. Besides
applying fuzzy logic in the main controller of a control loop, it can be used to design adaptive
control, tuning parameters, working in a parallel with the classical and non classical control
method. However the application area for fuzzy control is really wide, the basic form for all
command types of controllers consists of [10-15, 20, 36];
• Input fuzzification (binary-to-fuzzy[B/F]conversion)
• Fuzzy rule base (knowledge base)
• Inference engine
• Output defuzzification (fuzzy-to-binary[F/B]conversion).
As a summary the design of fuzzy logic controller based on Mamdani’s fuzzy inference method
has four steps, namely, fuzzification, fuzzy rule base and rule evaluation, aggregation of the rule
output (fuzzy inference system), and deffuzzification.
Fuzzification: the first step in fuzzification is determine inputs and outputs which, it has one input
( ) and one output ( ). The input is which measures the summation of linear loop and
nonlinear loop in main controller. The second step is chosen an appropriate membership function
for inputs and output which, for simplicity in implementation and also to have an acceptable
performance the researcher is selected the triangular membership function. The third step is
chosen the correct labels for each fuzzy set which, in this research namely as linguistic variable.
The linguistic variables for input ( ) are; Negative Big (NB), Negative Medium (NM), Negative
Small (NS), Zero (Z), Positive Small (PS), Positive Medium (PM), Positive Big (PB), and it is
quantized in to thirteen levels represented by: -1, -0.83, -0.66, -0.5, -0.33, -0.16, 0, 0.16, 0.33, 0.5,
0.66, 0.83, 1 and the linguistic variables to find the output are; Large Left (LL), Medium Left (ML),
Small Left (SL), Zero (Z), Small Right (SR), Medium Right (MR), Large Right (LR) and it is
quantized in to thirteen levels represented by: -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6.
Fuzzy Rule Base and Rule Evaluation: the first step in rule base and evaluation is provide a
least structured method to derive the fuzzy rule base which, expert experience and control
engineering knowledge is used because this method is the least structure of the other one and the
researcher derivation the fuzzy rule base from the knowledge of system operate and/or the
classical controller. Design the rule base of fuzzy inference system can play important role to
design the best performance of fuzzy sliding mode controller, that to calculate the fuzzy rule base
the researcher is used to heuristic method which, it is based on the behavior of the control of robot
manipulator suppose that the fuzzy rules in this controller is [36];
F.R
1
: IF is NB, THEN is LL. (13)
The complete rule base for this controller is shown in Table 1. Rule evaluation focuses on
operation in the antecedent of the fuzzy rules in fuzzy sliding mode controller. This part is used
fuzzy operation in antecedent part which operation is used.
Aggregation of the Rule Output (Fuzzy Inference): Max-Min aggregation is used to this work
which the calculation is defined as follows;
(14)
7. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 19
Deffuzzification: The last step to design fuzzy inference in our fuzzy sliding mode controller is
defuzzification. This part is used to transform fuzzy set to crisp set, therefore the input for
defuzzification is the aggregate output and the output of it is a crisp number. In this design the
Center of gravity method is used and calculated by the following equation [36];
(15)
This table has 7 cells, and used to describe the dynamics behavior of fuzzy controller.
NB NM NS Z PS PM PB
LL ML SL Z SR MR LR
TABLE 1: Rule table
Figure 2 is shown the feedback linearization fuzzy controller based on fuzzy logic controller and
minimum rule base.
FIGURE2: Block Diagram of inverse dynamic Fuzzy Controller with Minimum Rule Base
Second Step; Design Sliding Mode Fuzzy Adaptive Inverse Dynamic Fuzzy Controller With
Minimum Rules: All conventional controller have common difficulty, they need to find several
parameters. Tuning feedback linearization fuzzy method can tune automatically the scale
parameters using artificial intelligence method. To keep the structure of the controller as simple as
possible and to avoid heavy computation, a one input Mamdani sliding mode fuzzy supervisor
tuner is selected. In this method the tuneable controller tunes the PD coefficient inverse dynamic
controller using gain updating factors.
However proposed inverse dynamic fuzzy controller has satisfactory performance but calculates
the main controller coefficient by try and error or experience knowledge is very difficult,
particularly when system has uncertainties; sliding mode fuzzy adaptive inverse dynamic fuzzy
controller is recommended. The lyapunov formulation is defined by:
(16)
Where is positive coefficient,
Since is skew-symetric matrix, we can get
8. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 20
(17)
From following two functions:
(18)
And
(19)
We can get:
(20)
Since; then
(21)
The derivative of V defined by;
(22)
suppose is defined as follows
(23)
Where and
(24)
Based on
(25)
where is adaption law,
consequently can be considered by
(26)
If the minimum error can be defined by
(27)
is intended as follows
9. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 21
(28)
For continuous function , and suppose it is defined the fuzzy logic system in form of
the minimum approximation error is very small.
Figure 3 is shown the block diagram of proposed fuzzy adaptive applied to feedback linearization
fuzzy controller.
FIGURE 3: Design sliding mode fuzzy adaptive inverse dynamic fuzzy controller
4 SIMULATION RESULTS
Pure inverse dynamic controller (IDC) and sliding mode fuzzy adaptive inverse dynamic fuzzy
controller (SMFIDFC) are implemented in Matlab/Simulink environment. Tracking performance
and disturbance rejection is compared.
Tracking Performances: From the simulation for first, second and third trajectory without
any disturbance, it was seen that IDC and SMFIDFC have the same performance because this
system is worked on certain environment. The SMFIDFC gives significant trajectory good
following when compared to pure fuzzy logic controller. Figure 4 shows tracking performance
without any disturbance for IDC and SMFIDFC.
10. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 22
FIGURE 4 : IDC Vs. SMFIDFC: applied to 3DOF’s robot manipulator
By comparing sinus response trajectory without disturbance in IDC and SMFIDFC, it is found that
the SMFIDFC’s overshoot (0%) is lower than IDC's (3%) and the rise time in FAFLIFC’s (0.8 sec)
and FLIC’s (0.8 sec).
Disturbance Rejection: Figure 5 has shown the power disturbance elimination in IDC and
SMFIDFC. The main targets in these controllers are disturbance rejection as well as the other
responses. A band limited white noise with predefined of 40% the power of input signal is applied
to the IDC and SMFIDFC. It found fairly fluctuations in IDC trajectory responses.
11. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 23
FIGURE 5: IDC Vs. SMFIDFC: applied to robot manipulator.
Among above graph relating to trajectory following with external disturbance, IDC has fairly
fluctuations. By comparing some control parameters such as overshoot and rise time it found that
the SMFIDFC’s overshoot (0%) is lower than IDC’s (10%), although both of them have about the
same rise time.
5 CONCLUSIONS
In this research, sliding mode fuzzy Lyapunov based tuning inverse dynamic fuzzy methodology
to outline learns of this adaption gain is recommended. The study of stability for robot manipulator
with regard to applied artificial intelligence in robust classical method and adaptive sliding mode
fuzzy law in practice is considered to be a subject in this work. The system performance in inverse
dynamic controller and inverse dynamic fuzzy controller are sensitive to the main controller
coefficient. Compute the finest value of main controller coefficient for a system is the main
important challenge work. This problem has solved by adjusting main controller coefficient of the
inverse dynamic controller continuously on-line. Therefore, the overall system performance has
improved with respect to the pure inverse dynamic controller and inverse dynamic fuzzy controller.
As mentioned in previous, this controller solved external disturbance as well as mathematical
nonlinear equivalent part by applied sliding mode fuzzy supervisory controller in inverse dynamic
fuzzy controller. By comparing between sliding mode fuzzy adaptive inverse dynamic fuzzy
controller and inverse dynamic fuzzy controller, it found that sliding mode fuzzy adaptive inverse
dynamic fuzzy controller has steadily stabilised in response although inverse dynamic fuzzy
controller has small oscillation in the presence of structure and unstructured uncertainties.
REFERENCES
[1] Thomas R. Kurfess, Robotics and Automation Handbook: CRC press, 2005.
[2] Bruno Siciliano and Oussama Khatib, Handbook of Robotics: Springer, 2007.
12. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 24
[3] Slotine J. J. E., and W. Li., Applied nonlinear control: Prentice-Hall Inc, 1991.
[4] Piltan Farzin, et al., “Artificial Chattering Free on-line Fuzzy Sliding Mode Algorithm for
Uncertain System: Applied in Robot Manipulator,” International Journal of Engineering, 5
(5):220-238, 2011.
[5] L.X.Wang, “stable adaptive fuzzy control of nonlinear systems”, IEEE transactions on
fuzzy systems, 1(2): 146-154, 1993.
[6] Frank L.Lewis, Robot dynamics and control, in robot Handbook: CRC press, 1999.
[7] A.Vivas, V.Mosquera, “predictive functional control of puma robot”, ACSE05 conference,
2005.
[8] D.Tuong, M.Seeger, J.peters,” Computed torque control with nonparametric regressions
models”, American control conference, pp: 212-217, 2008.
[9] Piltan, F., et al., “Designing on-line Tunable Gain Fuzzy Sliding Mode Controller using
Sliding Mode Fuzzy Algorithm: Applied to Internal Combustion Engine,” World Applied
Sciences Journal , 14 (9): 1299-1305, 2011.
[10] Lotfi A. Zadeh” Toward a theory of fuzzy information granulation and its centrality in
human easoning and fuzzy logic” Fuzzy Sets and Systems 90 (1997) 111-127
[11] Reznik L., Fuzzy Controllers, First edition: BH NewNes, 1997.
[12] Zhou, J., Coiffet, P,” Fuzzy Control of Robots,” Proceedings IEEE International
Conference on Fuzzy Systems, pp: 1357 – 1364, 1992.
[13] Banerjee, S., Peng Yung Woo, “Fuzzy logic control of robot manipulator,” Proceedings
Second IEEE Conference on Control Applications, pp: 87 – 88, 1993.
[14] Akbarzadeh-T A. R., K.Kumbla, E. Tunstel, M. Jamshidi. ,”Soft Computing for
autonomous Robotic Systems,” IEEE International Conference on Systems, Man and
Cybernatics, pp: 5252-5258, 2000.
[15] Lee C.C.,” Fuzzy logic in control systems: Fuzzy logic controller-Part 1,” IEEE
International Conference on Systems, Man and Cybernetics, 20(2), P.P: 404-418, 1990.
[16] F. Piltan, et al., "Artificial Control of Nonlinear Second Order Systems Based on
AFGSMC," Australian Journal of Basic and Applied Sciences, 5(6), pp. 509-522, 2011.
[17] Piltan, F., et al., “Design sliding mode controller for robot manipulator with artificial tunable
gain,” Canaidian Journal of pure and applied science, 5 (2): 1573-1579, 2011.
[18] Piltan, F., et al., “Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC
with Tunable Gain,” International Journal of Robotic and Automation, 2 (3): 205-220,
2011.
[19] Piltan, F., et al., “Design of FPGA based sliding mode controller for robot manipulator,”
International Journal of Robotic and Automation, 2 (3): 183-204, 2011.
[20] Piltan Farzin, et al., “Design PID-Like Fuzzy Controller With Minimum Rule Base and
Mathematical Proposed On-line Tunable Gain: Applied to Robot Manipulator,”
International Journal of Artificial intelligence and expert system, 2 (4):184-195, 2011.
13. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 25
[21] Farzin Piltan, A. R. Salehi and Nasri B Sulaiman.,” Design artificial robust control of
second order system based on adaptive fuzzy gain scheduling,” world applied science
journal (WASJ), 13 (5): 1085-1092, 2011.
[22] Piltan, F., et al., “Design On-Line Tunable Gain Artificial Nonlinear Controller ,” Journal of
Advances In Computer Research , 2 (4): 19-28, 2011.
[23] Piltan, F., et al., “Design Mathematical Tunable Gain PID-Like Sliding Mode Fuzzy
Controller with Minimum Rule Base,” International Journal of Robotic and Automation, 2
(3): 146-156, 2011.
[24] Piltan Farzin, et al., “Design of PC-based sliding mode controller and normalized sliding
surface slope using PSO method for robot manipulator,” International Journal of Robotics
and Automation, 2 (4):245-260, 2011.
[25] Piltan, F., et al., “A Model Free Robust Sliding Surface Slope Adjustment in Sliding Mode
Control for Robot Manipulator,” World Applied Science Journal, 12 (12): 2330-2336,
2011.
[26] Piltan, F., et al., “Design Adaptive Fuzzy Robust Controllers for Robot Manipulator,”
World Applied Science Journal, 12 (12): 2317-2329, 2011.
[27] Piltan Farzin, et al., “ Design Model Free Fuzzy Sliding Mode Control: Applied to Internal
Combustion Engine,” International Journal of Engineering, 5 (4):302-312, 2011.
[28] Piltan Farzin, et al., “Design of PC-based sliding mode controller and normalized sliding
surface slope using PSO method for robot manipulator,” International Journal of Robotics
and Automation, 2 (4):245-260, 2011.
[29] Piltan, F., et al., “Design a New Sliding Mode Adaptive Hybrid Fuzzy Controller,” Journal
of Advanced Science & Engineering Research , 1 (1): 115-123, 2011.
[30] Piltan, F., et al., “Novel Sliding Mode Controller for robot manipulator using FPGA,”
Journal of Advanced Science & Engineering Research, 1 (1): 1-22, 2011.
[31] Piltan Farzin, et al., “Design of Model Free Adaptive Fuzzy Computed Torque Controller:
Applied to Nonlinear Second Order System,” International Journal of Robotics and
Automation, 2 (4):232-244, 2011.
[32] Piltan Farzin, et al., “Control of IC Engine: Design a Novel MIMO Fuzzy Backstepping
Adaptive Based Fuzzy Estimator Variable Structure Control ,” International Journal of
Robotics and Automation, 2 (5):357-370, 2011.
[33] Piltan, F., et al., “Adaptive MIMO Fuzzy Compensate Fuzzy Sliding Mode Algorithm:
Applied to Second Order Nonlinear System,” International Journal of Engineering, 5 (5):
249-263, 2011.
[34] Piltan, F., et al., “Novel Robot Manipulator Adaptive Artificial Control: Design a Novel
SISO Adaptive Fuzzy Sliding Algorithm Inverse Dynamic Like Method,” International
Journal of Engineering, 5 (5): 264-279, 2011.
[35] Piltan Farzin, et al., “Position Control of Robot Manipulator: Design a Novel SISO
Adaptive Sliding Mode Fuzzy PD Fuzzy Sliding Mode Control,” International Journal of
Artificial intelligence and Expert System, 2 (5):184-198, 2011.
14. Farzin Piltan, M.A. Bairami, F. Aghayari & S. Allahdadi
International Journal of Robotics and Automation (IJRA), Volume (3) : Issue (1) : 2011 26
[36] Piltan Farzin, et al., “Artificial Control of PUMA Robot Manipulator: A-Review of Fuzzy
Inference Engine And Application to Classical Controller,” International Journal of
Robotics and Automation, 2 (5):387-403, 2011.
[37] Piltan, F., et al., “Design Adaptive Fuzzy Inference Sliding Mode Algorithm: Applied to
Robot Arm,” International Journal of Robotics and Automation, 2 (5): 275-295, 2011.
[38] Piltan, F., et al., “Novel Artificial Control of Nonlinear Uncertain System: Design a Novel
Modified PSO SISO Lyapunov Based Fuzzy Sliding Mode Algorithm,” International
Journal of Robotics and Automation, 2 (5): 310-325, 2011.
[39] Piltan Farzin, et al., “Evolutionary Design of Mathematical tunable FPGA Based MIMO
Fuzzy Estimator Sliding Mode Based Lyapunov Algorithm: Applied to Robot Manipulator,”
International Journal of Robotics and Automation, 2 (5):340-356, 2011.
[40] Piltan Farzin, et al., “Evolutionary Design of Backstepping Artificial Sliding Mode Based
Position Algorithm: Applied to Robot Manipulator,” International Journal of Engineering, 5
(5):239-248, 2011.
[41] Piltan, F., et al., “An Adaptive sliding surface slope adjustment in PD Sliding Mode Fuzzy
Control for Robot Manipulator,” International Journal of Control and Automation , 4 (3): 65-
76, 2011.
[42] Piltan, F., et al., “Design PID-Like Fuzzy Controller with Minimum Rule base and
Mathematical proposed On-line Tunable Gain: applied to Robot manipulator,”
International Journal of Artificial Intelligence and Expert System, 2 (5): 195-210, 2011.
[43] Piltan Farzin, et al., “Design and Implementation of Sliding Mode Algorithm: Applied to
Robot Manipulator-A Review,” International Journal of Robotics and Automation, 2
(5):371-386, 2011.
[44] Piltan Farzin, et al., “Control of Robot Manipulator: Design a Novel Tuning MIMO Fuzzy
Backstepping Adaptive Based Fuzzy Estimator Variable Structure Control ,” International
Journal of Control and Automation, 4 (4):25-36, 2011.
[45] Piltan, F., et al., “Evolutionary Design on-line Sliding Fuzzy Gain Scheduling Sliding Mode
Algorithm: Applied to Internal Combustion Engine,” International journal of Engineering
Science and Technology , 3 (10): 7301-7308, 2011.
[46] Soltani Samira and Piltan, F. “Design artificial control based on computed torque like
controller with tunable gain,” World Applied Science Journal, 14 (9): 1306-1312, 2011.