This paper uses a fuzzy neural network (FNN) structure for identifying and controlling nonlinear dynamic systems such three links robot arm. The equation of motion for three links robot arm derived using Lagrange’s equation. This equation then combined with the equations of motion for dc. servo motors which actuated the robot. For the control problem, we present the forward and inverse adaptive control approaches using the FNN. Computer simulation is performed to view the results for identification and control
Solution of Inverse Kinematics for SCARA Manipulator Using Adaptive Neuro-Fuz...ijsc
Solution of inverse kinematic equations is complex problem, the complexity comes from the nonlinearity of joint space and Cartesian space mapping and having multiple solution. In this work, four adaptive neurofuzzy networks ANFIS are implemented to solve the inverse kinematics of 4-DOF SCARA manipulator. The implementation of ANFIS is easy, and the simulation of it shows that it is very fast and give acceptable
error.
A fuzzy logic controllerfora two link functional manipulatorIJCNCJournal
This paper presents a new approach for designing a Fuzzy Logic Controller "FLC"for a dynamically multivariable nonlinear coupling system. The conventional controller with constant gains for different operating points may not be sufficient to guarantee satisfactory performance for Robot manipulator. The Fuzzy Logic Controller utilizes the error and the change of error as fuzzy linguistic inputs to regulate the system performance. The proposed controller have been developed to simulate the dynamic behavior of A
Two-Link Functional Manipulator. The new controller uses only the available information of the input-output for controlling the position and velocity of the robot axes of the motion of the end effectors
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.
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.
—This paper presents a new image based visual servoing (IBVS) control scheme for omnidirectional wheeled mobile robots with four swedish wheels. The contribution is the proposal of a scheme that consider the overall dynamic of the system; this means, we put together mechanical and electrical dynamics. The actuators are direct current (DC) motors, which imply that the system input signals are armature voltage applied to DC motors. In our control scheme the PD control law and eye-to-hand camera configuration are used to compute the armature voltages and to measure system states, respectively. Stability proof is performed via Lypunov direct method and LaSalle's invariance principle. Simulation and experimental results were performed in order to validate the theoretical proposal and to show the good performance of the posture errors. Keywords—IBVS, posture control, omnidirectional wheeled mobile robot, dynamic actuator, Lyapunov direct method.
Adaptive Control of a Robotic Arm Using Neural Networks Based ApproachWaqas Tariq
A new neural networks and time series prediction based method has been discussed to control the complex nonlinear multi variable robotic arm motion system in 3d environment without engaging the complicated and voluminous dynamic equations of robotic arms in controller design stage, the proposed method gives such compatibility to the manipulator that it could have significant changes in its dynamic properties, like getting mechanical loads, without need to change designs of the controller.
Solution of Inverse Kinematics for SCARA Manipulator Using Adaptive Neuro-Fuz...ijsc
Solution of inverse kinematic equations is complex problem, the complexity comes from the nonlinearity of joint space and Cartesian space mapping and having multiple solution. In this work, four adaptive neurofuzzy networks ANFIS are implemented to solve the inverse kinematics of 4-DOF SCARA manipulator. The implementation of ANFIS is easy, and the simulation of it shows that it is very fast and give acceptable
error.
A fuzzy logic controllerfora two link functional manipulatorIJCNCJournal
This paper presents a new approach for designing a Fuzzy Logic Controller "FLC"for a dynamically multivariable nonlinear coupling system. The conventional controller with constant gains for different operating points may not be sufficient to guarantee satisfactory performance for Robot manipulator. The Fuzzy Logic Controller utilizes the error and the change of error as fuzzy linguistic inputs to regulate the system performance. The proposed controller have been developed to simulate the dynamic behavior of A
Two-Link Functional Manipulator. The new controller uses only the available information of the input-output for controlling the position and velocity of the robot axes of the motion of the end effectors
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.
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.
—This paper presents a new image based visual servoing (IBVS) control scheme for omnidirectional wheeled mobile robots with four swedish wheels. The contribution is the proposal of a scheme that consider the overall dynamic of the system; this means, we put together mechanical and electrical dynamics. The actuators are direct current (DC) motors, which imply that the system input signals are armature voltage applied to DC motors. In our control scheme the PD control law and eye-to-hand camera configuration are used to compute the armature voltages and to measure system states, respectively. Stability proof is performed via Lypunov direct method and LaSalle's invariance principle. Simulation and experimental results were performed in order to validate the theoretical proposal and to show the good performance of the posture errors. Keywords—IBVS, posture control, omnidirectional wheeled mobile robot, dynamic actuator, Lyapunov direct method.
Adaptive Control of a Robotic Arm Using Neural Networks Based ApproachWaqas Tariq
A new neural networks and time series prediction based method has been discussed to control the complex nonlinear multi variable robotic arm motion system in 3d environment without engaging the complicated and voluminous dynamic equations of robotic arms in controller design stage, the proposed method gives such compatibility to the manipulator that it could have significant changes in its dynamic properties, like getting mechanical loads, without need to change designs of the controller.
Simulation design of trajectory planning robot manipulatorjournalBEEI
Robots can be mathematically modeled with computer programs where the results can be displayed visually, so it can be used to determine the input, gain, attenuate and error parameters of the control system. In addition to the robot motion control system, to achieve the target points should need a research to get the best trajectory, so the movement of robots can be more efficient. One method that can be used to get the best path is the SOM (Self Organizing Maps) neural network. This research proposes the usage of SOM in combination with PID and Fuzzy-PD control for finding an optimal path between source and destination. SOM Neural network process is able to guide the robot manipulator through the target points. The results presented emphasize that a satisfactory trajectory tracking precision and stability could be achieved using SOM Neural networking combination with PID and Fuzzy-PD controller.The obtained average error to reach the target point when using Fuzzy-PD=2.225% and when using PID=1.965%.
Multilayer extreme learning machine for hand movement prediction based on ele...journalBEEI
Brain computer interface (BCI) technology connects humans with machines via electroencephalography (EEG). The mechanism of BCI is pattern recognition, which proceeds by feature extraction and classification. Various feature extraction and classification methods can differentiate human motor movements, especially those of the hand. Combinations of these methods can greatly improve the accuracy of the results. This article explores the performances of nine feature-extraction types computed by a multilayer extreme learning machine (ML-ELM). The proposed method was tested on different numbers of EEG channels and different ML-ELM structures. Moreover, the performance of ML-ELM was compared with those of ELM, Support Vector Machine and Naive Bayes in classifying real and imaginary hand movements in offline mode. The ML-ELM with discrete wavelet transform (DWT) as feature extraction outperformed the other classification methods with highest accuracy 0.98. So, the authors also found that the structures influenced the accuracy of ML-ELM for different task, feature extraction used and channel used.
Smart element aware gate controller for intelligent wheeled robot navigationIJECEIAES
The directing of a wheeled robot in an unknown moving environment with physical barriers is a difficult proposition. In particular, having an optimal or near-optimal path that avoids obstacles is a major challenge. In this paper, a modified neuro-controller mechanism is proposed for controlling the movement of an indoor mobile robot. The proposed mechanism is based on the design of a modified Elman neural network (MENN) with an effective element aware gate (MEEG) as the neuro-controller. This controller is updated to overcome the rigid and dynamic barriers in the indoor area. The proposed controller is implemented with a mobile robot known as Khepera IV in a practical manner. The practical results demonstrate that the proposed mechanism is very efficient in terms of providing shortest distance to reach the goal with maximum velocity as compared with the MENN. Specifically, the MEEG is better than MENN in minimizing the error rate by 58.33%.
Neural Network based Vehicle Classification for Intelligent Traffic Controlijseajournal
Nowadays, number of vehicles has been increased and traditional systems of traffic controlling couldn’t be
able to meet the needs that cause to emergence of Intelligent Traffic Controlling Systems. They improve
controlling and urban management and increase confidence index in roads and highways. The goal of this
article is vehicles classification base on neural networks. In this research, it has been used a immovable
camera which is located in nearly close height of the road surface to detect and classify the vehicles. The
algorithm that used is included two general phases; at first, we are obtaining mobile vehicles in the traffic
situations by using some techniques included image processing and remove background of the images and
performing edge detection and morphology operations. In the second phase, vehicles near the camera are
selected and the specific features are processed and extracted. These features apply to the neural networks
as a vector so the outputs determine type of vehicle. This presented model is able to classify the vehicles in
three classes; heavy vehicles, light vehicles and motorcycles. Results demonstrate accuracy of the
algorithm and its highly functional level.
Design and implementation of path planning algorithm for wheeled mobile robot...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Design and implementation of path planning algorithm for wheeled mobile robot...eSAT Journals
Abstract Path planning in mobile robots must ensure optimality of the path. The optimality achieved may be in path, time, energy consumed etc. Path planning in robots also depends on the environment in which it operates like, static or dynamic, known or unknown etc. Global path planning using A* algorithm and genetic algorithm is investigated in this paper. A known dynamic environment, in which a control station will compute the shortest path and communicate to the mobile robot and the mobile robot, will traverse through this path to reach the goal. The control station will keep track of the path traversed by the robot. The mobile robot navigates through the shortest path and if the robot detects any obstacle in the destined path, the mobile robot will update the information about the environment and this information together with the current location will be communicated to the control station. Then the control station, with the updated map of the environment and new starting location and destination recalculates the new shortest path, if any, and will communicate to the mobile robot so that it can reach the destination. The technique has been implemented and tested extensively in real-world experiments and simulation runs. The results demonstrate that the technique effectively calculates the shortest path in known dynamic environment and allows the robot to quickly accomplish the mission.
High - Performance using Neural Networks in Direct Torque Control for Asynchr...IJECEIAES
This article investigates solution for the biggest problem of the Direct Torque Control on the asynchronous machine to have the high dynamic performance with very simple hysteresis control scheme. The Conventional Direct Torque Control (CDTC) suffers from some drawbacks such as high current, flux and torque ripple, as well as flux control at very low speed. In this paper, we propose an intelligent approach to improve the direct torque control of induction machine which is an artificial neural networks control. The principle, the numerical procedure and the performances of this method are presented. Simulations results show that the proposed ANN-DTC strategy effectively reduces the torque and flux ripples at low switching frequency, compared with Fuzzy Logic DTC and The Conventional DTC.
Power system transient stability margin estimation using artificial neural ne...elelijjournal
This paper presents a methodology for estimating the normalized transient stability margin by using the multilayered perceptron (MLP) neural network. The complex relationship between the input variables and output variables is established by using the neural networks. The nonlinear mapping relation between the normalized transient stability margin and the operating conditions of the power system is established by using the MLP neural network. To obtain the training set of the neural network the potential energy boundary surface (PEBS) method along with time domain simulation method is used. The proposed method is applied on IEEE 9 bus system and the results shows that the proposed method provides fast and accurate tool to assess online transient stability.
International Journal of Research in Engineering and Science is an open access peer-reviewed international forum for scientists involved in research to publish quality and refereed papers. Papers reporting original research or experimentally proved review work are welcome. Papers for publication are selected through peer review to ensure originality, relevance, and readability.
Macromodel of High Speed Interconnect using Vector Fitting Algorithmijsrd.com
At high frequency efficient macromodeling of high speed interconnects is all time challenging task. We have presented systematic methodologies to generate rational function approximations of high-speed interconnects using vector fitting technique for any type of termination conditions and construct efficient multiport model, which is easily and directly compatible with circuit simulators.
An Investigation on Patrol Robot Coverage Performance Based on Chaotic and no...drboon
In some practical applications of the mobile robot, it is expected to ensure the fullest coverage of a certain area with or without obstacle avoidance. This paper shows that both chaotic and non chaotic signals can be advantageous for providing good coverage performance. Our study includes, in addition to parameters adjusting and mapping the appropriate chaotic variables to robot's kinematic variables, a comparison of the coverage performance generated by three different behaviors of Chua’s circuit. These behaviors include an instable focus and two chaotic signals having single scroll and double scroll shaped phase portraits respectively. Contrary to a commonly held belief, a non-chaotic behavior can lead to generate complex trajectories of a mobile robot and to provide better coverage performance. Such behavior is an instable focus which is a repeller, obtained by using a particular parameter set of Chua’s circuit.
Solution of Inverse Kinematics for SCARA Manipulator Using Adaptive Neuro-Fuz...ijsc
Solution of inverse kinematic equations is complex problem, the complexity comes from the nonlinearity of joint space and Cartesian space mapping and having multiple solution. In this work, four adaptive neurofuzzy networks ANFIS are implemented to solve the inverse kinematics of 4-DOF SCARA manipulator. The implementation of ANFIS is easy, and the simulation of it shows that it is very fast and give acceptable error.
Vibration and tip deflection control of a single link flexible manipulatorijics
In this paper, a hybrid control scheme for vibration and tip deflection control of a single link flexible
manipulator system is presented. The purpose of this control is for input tracking, vibration control of hub
angle and tip deflection control. The control scheme consists of a resonant controller and a fuzzy logic
controller (FLC).The resonant controller is used as the inner loop feedback controller for vibration control
using the resonant frequencies at different resonant modes of the system which were determined from
experiment. The fuzzy logic controller is designed as the outer loop feedback controller for the tracking
control and to achieve zero steady state error. The performance of the proposed control scheme is
investigated via simulations and the results show the effectiveness of the control scheme, in addition the
controller is tested to show it robustness using different values of payload.
Simulation design of trajectory planning robot manipulatorjournalBEEI
Robots can be mathematically modeled with computer programs where the results can be displayed visually, so it can be used to determine the input, gain, attenuate and error parameters of the control system. In addition to the robot motion control system, to achieve the target points should need a research to get the best trajectory, so the movement of robots can be more efficient. One method that can be used to get the best path is the SOM (Self Organizing Maps) neural network. This research proposes the usage of SOM in combination with PID and Fuzzy-PD control for finding an optimal path between source and destination. SOM Neural network process is able to guide the robot manipulator through the target points. The results presented emphasize that a satisfactory trajectory tracking precision and stability could be achieved using SOM Neural networking combination with PID and Fuzzy-PD controller.The obtained average error to reach the target point when using Fuzzy-PD=2.225% and when using PID=1.965%.
Multilayer extreme learning machine for hand movement prediction based on ele...journalBEEI
Brain computer interface (BCI) technology connects humans with machines via electroencephalography (EEG). The mechanism of BCI is pattern recognition, which proceeds by feature extraction and classification. Various feature extraction and classification methods can differentiate human motor movements, especially those of the hand. Combinations of these methods can greatly improve the accuracy of the results. This article explores the performances of nine feature-extraction types computed by a multilayer extreme learning machine (ML-ELM). The proposed method was tested on different numbers of EEG channels and different ML-ELM structures. Moreover, the performance of ML-ELM was compared with those of ELM, Support Vector Machine and Naive Bayes in classifying real and imaginary hand movements in offline mode. The ML-ELM with discrete wavelet transform (DWT) as feature extraction outperformed the other classification methods with highest accuracy 0.98. So, the authors also found that the structures influenced the accuracy of ML-ELM for different task, feature extraction used and channel used.
Smart element aware gate controller for intelligent wheeled robot navigationIJECEIAES
The directing of a wheeled robot in an unknown moving environment with physical barriers is a difficult proposition. In particular, having an optimal or near-optimal path that avoids obstacles is a major challenge. In this paper, a modified neuro-controller mechanism is proposed for controlling the movement of an indoor mobile robot. The proposed mechanism is based on the design of a modified Elman neural network (MENN) with an effective element aware gate (MEEG) as the neuro-controller. This controller is updated to overcome the rigid and dynamic barriers in the indoor area. The proposed controller is implemented with a mobile robot known as Khepera IV in a practical manner. The practical results demonstrate that the proposed mechanism is very efficient in terms of providing shortest distance to reach the goal with maximum velocity as compared with the MENN. Specifically, the MEEG is better than MENN in minimizing the error rate by 58.33%.
Neural Network based Vehicle Classification for Intelligent Traffic Controlijseajournal
Nowadays, number of vehicles has been increased and traditional systems of traffic controlling couldn’t be
able to meet the needs that cause to emergence of Intelligent Traffic Controlling Systems. They improve
controlling and urban management and increase confidence index in roads and highways. The goal of this
article is vehicles classification base on neural networks. In this research, it has been used a immovable
camera which is located in nearly close height of the road surface to detect and classify the vehicles. The
algorithm that used is included two general phases; at first, we are obtaining mobile vehicles in the traffic
situations by using some techniques included image processing and remove background of the images and
performing edge detection and morphology operations. In the second phase, vehicles near the camera are
selected and the specific features are processed and extracted. These features apply to the neural networks
as a vector so the outputs determine type of vehicle. This presented model is able to classify the vehicles in
three classes; heavy vehicles, light vehicles and motorcycles. Results demonstrate accuracy of the
algorithm and its highly functional level.
Design and implementation of path planning algorithm for wheeled mobile robot...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Design and implementation of path planning algorithm for wheeled mobile robot...eSAT Journals
Abstract Path planning in mobile robots must ensure optimality of the path. The optimality achieved may be in path, time, energy consumed etc. Path planning in robots also depends on the environment in which it operates like, static or dynamic, known or unknown etc. Global path planning using A* algorithm and genetic algorithm is investigated in this paper. A known dynamic environment, in which a control station will compute the shortest path and communicate to the mobile robot and the mobile robot, will traverse through this path to reach the goal. The control station will keep track of the path traversed by the robot. The mobile robot navigates through the shortest path and if the robot detects any obstacle in the destined path, the mobile robot will update the information about the environment and this information together with the current location will be communicated to the control station. Then the control station, with the updated map of the environment and new starting location and destination recalculates the new shortest path, if any, and will communicate to the mobile robot so that it can reach the destination. The technique has been implemented and tested extensively in real-world experiments and simulation runs. The results demonstrate that the technique effectively calculates the shortest path in known dynamic environment and allows the robot to quickly accomplish the mission.
High - Performance using Neural Networks in Direct Torque Control for Asynchr...IJECEIAES
This article investigates solution for the biggest problem of the Direct Torque Control on the asynchronous machine to have the high dynamic performance with very simple hysteresis control scheme. The Conventional Direct Torque Control (CDTC) suffers from some drawbacks such as high current, flux and torque ripple, as well as flux control at very low speed. In this paper, we propose an intelligent approach to improve the direct torque control of induction machine which is an artificial neural networks control. The principle, the numerical procedure and the performances of this method are presented. Simulations results show that the proposed ANN-DTC strategy effectively reduces the torque and flux ripples at low switching frequency, compared with Fuzzy Logic DTC and The Conventional DTC.
Power system transient stability margin estimation using artificial neural ne...elelijjournal
This paper presents a methodology for estimating the normalized transient stability margin by using the multilayered perceptron (MLP) neural network. The complex relationship between the input variables and output variables is established by using the neural networks. The nonlinear mapping relation between the normalized transient stability margin and the operating conditions of the power system is established by using the MLP neural network. To obtain the training set of the neural network the potential energy boundary surface (PEBS) method along with time domain simulation method is used. The proposed method is applied on IEEE 9 bus system and the results shows that the proposed method provides fast and accurate tool to assess online transient stability.
International Journal of Research in Engineering and Science is an open access peer-reviewed international forum for scientists involved in research to publish quality and refereed papers. Papers reporting original research or experimentally proved review work are welcome. Papers for publication are selected through peer review to ensure originality, relevance, and readability.
Macromodel of High Speed Interconnect using Vector Fitting Algorithmijsrd.com
At high frequency efficient macromodeling of high speed interconnects is all time challenging task. We have presented systematic methodologies to generate rational function approximations of high-speed interconnects using vector fitting technique for any type of termination conditions and construct efficient multiport model, which is easily and directly compatible with circuit simulators.
An Investigation on Patrol Robot Coverage Performance Based on Chaotic and no...drboon
In some practical applications of the mobile robot, it is expected to ensure the fullest coverage of a certain area with or without obstacle avoidance. This paper shows that both chaotic and non chaotic signals can be advantageous for providing good coverage performance. Our study includes, in addition to parameters adjusting and mapping the appropriate chaotic variables to robot's kinematic variables, a comparison of the coverage performance generated by three different behaviors of Chua’s circuit. These behaviors include an instable focus and two chaotic signals having single scroll and double scroll shaped phase portraits respectively. Contrary to a commonly held belief, a non-chaotic behavior can lead to generate complex trajectories of a mobile robot and to provide better coverage performance. Such behavior is an instable focus which is a repeller, obtained by using a particular parameter set of Chua’s circuit.
Solution of Inverse Kinematics for SCARA Manipulator Using Adaptive Neuro-Fuz...ijsc
Solution of inverse kinematic equations is complex problem, the complexity comes from the nonlinearity of joint space and Cartesian space mapping and having multiple solution. In this work, four adaptive neurofuzzy networks ANFIS are implemented to solve the inverse kinematics of 4-DOF SCARA manipulator. The implementation of ANFIS is easy, and the simulation of it shows that it is very fast and give acceptable error.
Vibration and tip deflection control of a single link flexible manipulatorijics
In this paper, a hybrid control scheme for vibration and tip deflection control of a single link flexible
manipulator system is presented. The purpose of this control is for input tracking, vibration control of hub
angle and tip deflection control. The control scheme consists of a resonant controller and a fuzzy logic
controller (FLC).The resonant controller is used as the inner loop feedback controller for vibration control
using the resonant frequencies at different resonant modes of the system which were determined from
experiment. The fuzzy logic controller is designed as the outer loop feedback controller for the tracking
control and to achieve zero steady state error. The performance of the proposed control scheme is
investigated via simulations and the results show the effectiveness of the control scheme, in addition the
controller is tested to show it robustness using different values of payload.
A COMPARATIVE ANALYSIS OF FUZZY BASED HYBRID ANFIS CONTROLLER FOR STABILIZATI...ijscmcjournal
This paper illustrates a Comparative study of highly non-linear, complex and multivariable Inverted
Pendulum (IP) system on Cart using different soft computing techniques. Firstly, a Fuzzy logic controller
was designed using triangular and trapezoidal shape Membership functions (MF's). The trapezoidal fuzzy
controller shows better results in comparison to triangular fuzzy controller. Secondly, an Adaptive neuro
fuzzy inference system (ANFIS) controller was used to optimize the results obtained from trapezoidal fuzzy
controller. Finally, the study illustrates the effect of variation in shape of MF's on Performance parameters
of the IP system. The results shows that ANFIS controller provides better results in comparison to both
fuzzy controller.
A Comparative Analysis of Fuzzy Based Hybrid Anfis Controller for Stabilizati...ijscmcj
This paper illustrates a Comparative study of highly non-linear, complex and multivariable Inverted Pendulum (IP) system on Cart using different soft computing techniques. Firstly, a Fuzzy logic controller was designed using triangular and trapezoidal shape Membership functions (MF's). The trapezoidal fuzzy controller shows better results in comparison to triangular fuzzy controller. Secondly, an Adaptive neuro fuzzy inference system (ANFIS) controller was used to optimize the results obtained from trapezoidal fuzzy controller. Finally, the study illustrates the effect of variation in shape of MF's on Performance parameters of the IP system. The results shows that ANFIS controller provides better results in comparison to both fuzzy controller.
INVERSIONOF MAGNETIC ANOMALIES DUE TO 2-D CYLINDRICAL STRUCTURES –BY AN ARTIF...ijsc
Application of Artificial Neural Network Committee Machine (ANNCM) for the inversion of magnetic
anomalies caused by a long-2D horizontal circular cylinder is presented. Although, the subsurface targets
are of arbitrary shape, they are assumed to be regular geometrical shape for convenience of mathematical
analysis. ANNCM inversion extract the parameters of the causative subsurface targets include depth to the
centre of the cylinder (Z), the inclination of magnetic vector(Ɵ)and the constant term (A)comprising the
radius(R)and the intensity of the magnetic field(I). The method of inversion is demonstrated over a
theoretical model with and without random noise in order to study the effect of noise on the technique and
then extended to real field data. It is noted that the method under discussion ensures fairly accurate results
even in the presence of noise. ANNCM analysis of vertical magnetic anomaly near Karimnagar, Telangana,
India, has shown satisfactory results in comparison with other inversion techniques that are in vogue.The
statistics of the predicted parameters relative to the measured data, show lower sum error (<9.58%) and
higher correlation coefficient (R>91%) indicating that good matching and correlation is achieved between
the measured and predicted parameters.
INVERSIONOF MAGNETIC ANOMALIES DUE TO 2-D CYLINDRICAL STRUCTURES –BY AN ARTIF...ijsc
Application of Artificial Neural Network Committee Machine (ANNCM) for the inversion of magnetic
anomalies caused by a long-2D horizontal circular cylinder is presented. Although, the subsurface targets
are of arbitrary shape, they are assumed to be regular geometrical shape for convenience of mathematical
analysis. ANNCM inversion extract the parameters of the causative subsurface targets include depth to the
centre of the cylinder (Z), the inclination of magnetic vector(Ɵ)and the constant term (A)comprising the
radius(R)and the intensity of the magnetic field(I). The method of inversion is demonstrated over a
theoretical model with and without random noise in order to study the effect of noise on the technique and
then extended to real field data. It is noted that the method under discussion ensures fairly accurate results
even in the presence of noise. ANNCM analysis of vertical magnetic anomaly near Karimnagar, Telangana,
India, has shown satisfactory results in comparison with other inversion techniques that are in vogue.The
statistics of the predicted parameters relative to the measured data, show lower sum error (<9.58%) and
higher correlation coefficient (R>91%) indicating that good matching and correlation is achieved between
the measured and predicted parameters.
Inversion of Magnetic Anomalies Due to 2-D Cylindrical Structures – By an Art...ijsc
Application of Artificial Neural Network Committee Machine (ANNCM) for the inversion of magnetic anomalies caused by a long-2D horizontal circular cylinder is presented. Although, the subsurface targets are of arbitrary shape, they are assumed to be regular geometrical shape for convenience of mathematical analysis. ANNCM inversion extract the parameters of the causative subsurface targets include depth to the centre of the cylinder (Z), the inclination of magnetic vector(Ɵ)and the constant term (A)comprising the radius(R)and the intensity of the magnetic field(I). The method of inversion is demonstrated over a theoretical model with and without random noise in order to study the effect of noise on the technique and then extended to real field data. It is noted that the method under discussion ensures fairly accurate results even in the presence of noise. ANNCM analysis of vertical magnetic anomaly near Karimnagar, Telangana, India, has shown satisfactory results in comparison with other inversion techniques that are in vogue.The statistics of the predicted parameters relative to the measured data, show lower sum error (<9.58%) and higher correlation coefficient (R>91%) indicating that good matching and correlation is achieved between the measured and predicted parameters.
Dynamics and control of a robotic arm having four linksAmin A. Mohammed
Abstract The manipulator control is an important problem
in robotics. To work out this problem, a correct dynamic
model for the robot manipulator must be in hand. Hence, this
work first presents the dynamic model of an existing 4-DOF
robot manipulator based on the Euler–Lagrange principle,
utilizing the body Jacobian of each link and the generalized
inertia matrix. Furthermore, essential properties of the
dynamic model are analyzed for the purpose of control. Then,
a PID controller is designed to control the position of the
robot by decoupling the dynamic model. To achieve a good
performance, the differential evolution algorithm is used for
the selection of parameters of the PID controller. Feedback
linearization scheme is also utilized for the position and trajectory
tracking control of the manipulator. The obtained
results reveal that the PID control coupled with the differential
evolution algorithm and the feedback linearization
control enhance the performance of the robotic manipulator.
It is also found out that increasing masses of manipulator
links do not affect the performance of the PID position control,
but higher control torques are required in these cases.
Keywords Robot control · PID · Differential evolution ·
Feedback linearization
Adaptive Fuzzy-Neural Control Utilizing Sliding Mode Based Learning Algorithm...IJERA Editor
This paper introduces an adaptive fuzzy-neural control (AFNC) utilizing sliding mode-based learning algorithm
(SMBLA) for robot manipulator to track the desired trajectory. A traditional sliding mode controller is applied to
ensure the asymptotic stability of the system, and the fuzzy rule-based wavelet neural networks (FWNNs) are
employed as the feedback controllers. Additionally, a novel adaptation of the FWNNs parameters is derived
from the SMBLA in the Lyapunov stability theorem. Hence, the AFNC approximates parameter variation,
unmodeled dynamics, and unknown disturbances without the detailed knowledge of robot manipulator, while
resulting in an improved tracking performance. Lastly, in order to validate the effectiveness of the proposed
approach, the comparative simulation results of two-degrees of freedom robot manipulator are presented.
Co-simulation of self-adjusting fuzzy PI controller for the robot with two-ax...TELKOMNIKA JOURNAL
This paper presents the co-simulation of the self-adjusting fuzzy PI controller to control a two-axes system. Each axis was driven by a permanent magnet linear synchronous motor (PMLSM). The position and speed controller used the fuzzy PI algorithm with parameters adjusted by a radial basis function neural network (RBFNN). The vector control was applied to the decoupled effect of the PMLSM. The field programmable gate array (FPGA) was used to control both axes of the system. The very high-speed integrated circuit-hardware description language (VHDL) was developed in the Quartus II software environment, provided by Altera, to analyze and synthesize designs. Firstly, the mathematical model of PMLSM and fuzzy PI was introduced. Secondly, the RBFNN adjusted the knowledge base of the fuzzy PI. Thirdly, the motion trajectory was introduced for testing the control algorithm. Fourthly, the implementation of the controller based on FPGA with the FSM method and the structure of co-simulation between Matlab/Simulink and ModelSim were set up. Finally, discussion about the results proved the effectiveness of the control system, determining the exact position and trajectory of the XY axis system. This research was successful in implementing a two-motor controller within one chip.
New artificial neural network design for Chua chaotic system prediction usin...IJECEIAES
This study aims to design a new architecture of the artificial neural networks (ANNs) using the Xilinx system generator (XSG) and its hardware co-simulation equivalent model using field programmable gate array (FPGA) to predict the behavior of Chua’s chaotic system and use it in hiding information. The work proposed consists of two main sections. In the first section, MATLAB R2016a was used to build a 3×4×3 feed forward neural network (FFNN). The training results demonstrate that FFNN training in the Bayesian regulation algorithm is sufficiently accurate to directly implement. The second section demonstrates the hardware implementation of the network with the XSG on the Xilinx artix7 xc7a100t-1csg324 chip. Finally, the message was first encrypted using a dynamic Chua system and then decrypted using ANN’s chaotic dynamics. ANN models were developed to implement hardware in the FPGA system using the IEEE 754 Single precision floating-point format. The ANN design method illustrated can be extended to other chaotic systems in general.
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
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).
The Use of Java Swing’s Components to Develop a WidgetWaqas Tariq
Widget is a kind of application provides a single service such as a map, news feed, simple clock, battery-life indicators, etc. This kind of interactive software object has been developed to facilitate user interface (UI) design. A user interface (UI) function may be implemented using different widgets with the same function. In this article, we present the widget as a platform that is generally used in various applications, such as in desktop, web browser, and mobile phone. We also describe a visual menu of Java Swing’s components that will be used to establish widget. It will assume that we have successfully compiled and run a program that uses Swing components.
3D Human Hand Posture Reconstruction Using a Single 2D ImageWaqas Tariq
Passive sensing of the 3D geometric posture of the human hand has been studied extensively over the past decade. However, these research efforts have been hampered by the computational complexity caused by inverse kinematics and 3D reconstruction. In this paper, our objective focuses on 3D hand posture estimation based on a single 2D image with aim of robotic applications. We introduce the human hand model with 27 degrees of freedom (DOFs) and analyze some of its constraints to reduce the DOFs without any significant degradation of performance. A novel algorithm to estimate the 3D hand posture from eight 2D projected feature points is proposed. Experimental results using real images confirm that our algorithm gives good estimates of the 3D hand pose. Keywords: 3D hand posture estimation; Model-based approach; Gesture recognition; human- computer interface; machine vision.
Camera as Mouse and Keyboard for Handicap Person with Troubleshooting Ability...Waqas Tariq
Camera mouse has been widely used for handicap person to interact with computer. The utmost important of the use of camera mouse is must be able to replace all roles of typical mouse and keyboard. It must be able to provide all mouse click events and keyboard functions (include all shortcut keys) when it is used by handicap person. Also, the use of camera mouse must allow users troubleshooting by themselves. Moreover, it must be able to eliminate neck fatigue effect when it is used during long period. In this paper, we propose camera mouse system with timer as left click event and blinking as right click event. Also, we modify original screen keyboard layout by add two additional buttons (button “drag/ drop” is used to do drag and drop of mouse events and another button is used to call task manager (for troubleshooting)) and change behavior of CTRL, ALT, SHIFT, and CAPS LOCK keys in order to provide shortcut keys of keyboard. Also, we develop recovery method which allows users go from camera and then come back again in order to eliminate neck fatigue effect. The experiments which involve several users have been done in our laboratory. The results show that the use of our camera mouse able to allow users do typing, left and right click events, drag and drop events, and troubleshooting without hand. By implement this system, handicap person can use computer more comfortable and reduce the dryness of eyes.
A Proposed Web Accessibility Framework for the Arab DisabledWaqas Tariq
The Web is providing unprecedented access to information and interaction for people with disabilities. This paper presents a Web accessibility framework which offers the ease of the Web accessing for the disabled Arab users and facilitates their lifelong learning as well. The proposed framework system provides the disabled Arab user with an easy means of access using their mother language so they don’t have to overcome the barrier of learning the target-spoken language. This framework is based on analyzing the web page meta-language, extracting its content and reformulating it in a suitable format for the disabled users. The basic objective of this framework is supporting the equal rights of the Arab disabled people for their access to the education and training with non disabled people. Key Words : Arabic Moon code, Arabic Sign Language, Deaf, Deaf-blind, E-learning Interactivity, Moon code, Web accessibility , Web framework , Web System, WWW.
Real Time Blinking Detection Based on Gabor FilterWaqas Tariq
New method of blinking detection is proposed. The utmost important of blinking detections method is robust against different users, noise, and also change of eye shape. In this paper, we propose blinking detections method by measuring of distance between two arcs of eye (upper part and lower part). We detect eye arcs by apply Gabor filter onto eye image. As we know that Gabor filter has advantage on image processing application since it able to extract spatial localized spectral features, such line, arch, and other shape are more easily detected. After two of eye arcs are detected, we measure the distance between both by using connected labeling method. The open eye is marked by the distance between two arcs is more than threshold and otherwise, the closed eye is marked by the distance less than threshold. The experiment result shows that our proposed method robust enough against different users, noise, and eye shape changes with perfectly accuracy.
Computer Input with Human Eyes-Only Using Two Purkinje Images Which Works in ...Waqas Tariq
A method for computer input with human eyes-only using two Purkinje images which works in a real time basis without calibration is proposed. Experimental results shows that cornea curvature can be estimated by using two light sources derived Purkinje images so that no calibration for reducing person-to-person difference of cornea curvature. It is found that the proposed system allows usersf movements of 30 degrees in roll direction and 15 degrees in pitch direction utilizing detected face attitude which is derived from the face plane consisting three feature points on the face, two eyes and nose or mouth. Also it is found that the proposed system does work in a real time basis.
Toward a More Robust Usability concept with Perceived Enjoyment in the contex...Waqas Tariq
Mobile multimedia service is relatively new but has quickly dominated people¡¯s lives, especially among young people. To explain this popularity, this study applies and modifies the Technology Acceptance Model (TAM) to propose a research model and conduct an empirical study. The goal of study is to examine the role of Perceived Enjoyment (PE) and what determinants can contribute to PE in the context of using mobile multimedia service. The result indicates that PE is influencing on Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) and directly Behavior Intention (BI). Aesthetics and flow are key determinants to explain Perceived Enjoyment (PE) in mobile multimedia usage.
Collaborative Learning of Organisational KnolwedgeWaqas Tariq
This paper presents recent research into methods used in Australian Indigenous Knowledge sharing and looks at how these can support the creation of suitable collaborative envi- ronments for timely organisational learning. The protocols and practices as used today and in the past by Indigenous communities are presented and discussed in relation to their relevance to a personalised system of knowledge sharing in modern organisational cultures. This research focuses on user models, knowledge acquisition and integration of data for constructivist learning in a networked repository of or- ganisational knowledge. The data collected in the repository is searched to provide collections of up-to-date and relevant material for training in a work environment. The aim is to improve knowledge collection and sharing in a team envi- ronment. This knowledge can then be collated into a story or workflow that represents the present knowledge in the organisation.
Our research aims to propose a global approach for specification, design and verification of context awareness Human Computer Interface (HCI). This is a Model Based Design approach (MBD). This methodology describes the ubiquitous environment by ontologies. OWL is the standard used for this purpose. The specification and modeling of Human-Computer Interaction are based on Petri nets (PN). This raises the question of representation of Petri nets with XML. We use for this purpose, the standard of modeling PNML. In this paper, we propose an extension of this standard for specification, generation and verification of HCI. This extension is a methodological approach for the construction of PNML with Petri nets. The design principle uses the concept of composition of elementary structures of Petri nets as PNML Modular. The objective is to obtain a valid interface through verification of properties of elementary Petri nets represented with PNML.
Development of Sign Signal Translation System Based on Altera’s FPGA DE2 BoardWaqas Tariq
The main aim of this paper is to build a system that is capable of detecting and recognizing the hand gesture in an image captured by using a camera. The system is built based on Altera’s FPGA DE2 board, which contains a Nios II soft core processor. Image processing techniques and a simple but effective algorithm are implemented to achieve this purpose. Image processing techniques are used to smooth the image in order to ease the subsequent processes in translating the hand sign signal. The algorithm is built for translating the numerical hand sign signal and the result are displayed on the seven segment display. Altera’s Quartus II, SOPC Builder and Nios II EDS software are used to construct the system. By using SOPC Builder, the related components on the DE2 board can be interconnected easily and orderly compared to traditional method that requires lengthy source code and time consuming. Quartus II is used to compile and download the design to the DE2 board. Then, under Nios II EDS, C programming language is used to code the hand sign translation algorithm. Being able to recognize the hand sign signal from images can helps human in controlling a robot and other applications which require only a simple set of instructions provided a CMOS sensor is included in the system.
An overview on Advanced Research Works on Brain-Computer InterfaceWaqas Tariq
A brain–computer interface (BCI) is a proficient result in the research field of human- computer synergy, where direct articulation between brain and an external device occurs resulting in augmenting, assisting and repairing human cognitive. Advanced works like generating brain-computer interface switch technologies for intermittent (or asynchronous) control in natural environments or developing brain-computer interface by Fuzzy logic Systems or by implementing wavelet theory to drive its efficacies are still going on and some useful results has also been found out. The requirements to develop this brain machine interface is also growing day by day i.e. like neuropsychological rehabilitation, emotion control, etc. An overview on the control theory and some advanced works on the field of brain machine interface are shown in this paper.
Exploring the Relationship Between Mobile Phone and Senior Citizens: A Malays...Waqas Tariq
There is growing ageing phenomena with the rise of ageing population throughout the world. According to the World Health Organization (2002), the growing ageing population indicates 694 million, or 223% is expected for people aged 60 and over, since 1970 and 2025.The growth is especially significant in some advanced countries such as North America, Japan, Italy, Germany, United Kingdom and so forth. This growing older adult population has significantly impact the social-culture, lifestyle, healthcare system, economy, infrastructure and government policy of a nation. However, there are limited research studies on the perception and usage of a mobile phone and its service for senior citizens in a developing nation like Malaysia. This paper explores the relationship between mobile phones and senior citizens in Malaysia from the perspective of a developing country. We conducted an exploratory study using contextual interviews with 5 senior citizens of how they perceive their mobile phones. This paper reveals 4 interesting themes from this preliminary study, in addition to the findings of the desirable mobile requirements for local senior citizens with respect of health, safety and communication purposes. The findings of this study bring interesting insight to local telecommunication industries as a whole, and will also serve as groundwork for more in-depth study in the future.
Principles of Good Screen Design in WebsitesWaqas Tariq
Visual techniques for proper arrangement of the elements on the user screen have helped the designers to make the screen look good and attractive. Several visual techniques emphasize the arrangement and ordering of the screen elements based on particular criteria for best appearance of the screen. This paper investigates few significant visual techniques in various web user interfaces and showcases the results for better understanding and their presence.
Virtual teams are used more and more by companies and other organizations to receive benefits. They are a great way to enable teamwork in situations where people are not sitting in the same physical place at the same time. As companies seek to increase the use of virtual teams, a need exists to explore the context of these teams, the virtuality of a team and software that may help these teams working virtualy. Virtual teams have the same basic principles as traditional teams, but there is one big difference. This difference is the way the team members communicate. Instead of using the dynamics of in-office face-to-face exchange, they now rely on special communication channels enabled by modern technologies, such as e-mails, faxes, phone calls and teleconferences, virtual meetings etc. This is why this paper is focused on the issues regarding virtual teams, and how these teams are created and progressing in Albania.
Cognitive Approach Towards the Maintenance of Web-Sites Through Quality Evalu...Waqas Tariq
It is a well established fact that the Web-Applications require frequent maintenance because of cutting– edge business competitions. The authors have worked on quality evaluation of web-site of Indian ecommerce domain. As a result of that work they have made a quality-wise ranking of these sites. According to their work and also the survey done by various other groups Futurebazaar web-site is considered to be one of the best Indian e-shopping sites. In this research paper the authors are assessing the maintenance of the same site by incorporating the problems incurred during this evaluation. This exercise gives a real world maintainability problem of web-sites. This work will give a clear picture of all the quality metrics which are directly or indirectly related with the maintainability of the web-site.
USEFul: A Framework to Mainstream Web Site Usability through Automated Evalua...Waqas Tariq
A paradox has been observed whereby web site usability is proven to be an essential element in a web site, yet at the same time there exist an abundance of web pages with poor usability. This discrepancy is the result of limitations that are currently preventing web developers in the commercial sector from producing usable web sites. In this paper we propose a framework whose objective is to alleviate this problem by automating certain aspects of the usability evaluation process. Mainstreaming comes as a result of automation, therefore enabling a non-expert in the field of usability to conduct the evaluation. This results in reducing the costs associated with such evaluation. Additionally, the framework allows the flexibility of adding, modifying or deleting guidelines without altering the code that references them since the guidelines and the code are two separate components. A comparison of the evaluation results carried out using the framework against published evaluations of web sites carried out by web site usability professionals reveals that the framework is able to automatically identify the majority of usability violations. Due to the consistency with which it evaluates, it identified additional guideline-related violations that were not identified by the human evaluators.
Robot Arm Utilized Having Meal Support System Based on Computer Input by Huma...Waqas Tariq
A robot arm utilized having meal support system based on computer input by human eyes only is proposed. The proposed system is developed for handicap/disabled persons as well as elderly persons and tested with able persons with several shapes and size of eyes under a variety of illumination conditions. The test results with normal persons show the proposed system does work well for selection of the desired foods and for retrieve the foods as appropriate as usersf requirements. It is found that the proposed system is 21% much faster than the manually controlled robotics.
Dynamic Construction of Telugu Speech Corpus for Voice Enabled Text EditorWaqas Tariq
In recent decades speech interactive systems have gained increasing importance. Performance of an ASR system mainly depends on the availability of large corpus of speech. The conventional method of building a large vocabulary speech recognizer for any language uses a top-down approach to speech. This approach requires large speech corpus with sentence or phoneme level transcription of the speech utterances. The transcriptions must also include different speech order so that the recognizer can build models for all the sounds present. But, for Telugu language, because of its complex nature, a very large, well annotated speech database is very difficult to build. It is very difficult, if not impossible, to cover all the words of any Indian language, where each word may have thousands and millions of word forms. A significant part of grammar that is handled by syntax in English (and other similar languages) is handled within morphology in Telugu. Phrases including several words (that is, tokens) in English would be mapped on to a single word in Telugu.Telugu language is phonetic in nature in addition to rich in morphology. That is why the speech technology developed for English cannot be applied to Telugu language. This paper highlights the work carried out in an attempt to build a voice enabled text editor with capability of automatic term suggestion. Main claim of the paper is the recognition enhancement process developed by us for suitability of highly inflecting, rich morphological languages. This method results in increased speech recognition accuracy with very much reduction in corpus size. It also adapts Telugu words to the database dynamically, resulting in growth of the corpus.
An Improved Approach for Word Ambiguity RemovalWaqas Tariq
Word ambiguity removal is a task of removing ambiguity from a word, i.e. correct sense of word is identified from ambiguous sentences. This paper describes a model that uses Part of Speech tagger and three categories for word sense disambiguation (WSD). Human Computer Interaction is very needful to improve interactions between users and computers. For this, the Supervised and Unsupervised methods are combined. The WSD algorithm is used to find the efficient and accurate sense of a word based on domain information. The accuracy of this work is evaluated with the aim of finding best suitable domain of word. Keywords: Human Computer Interaction, Supervised Training, Unsupervised Learning, Word Ambiguity, Word sense disambiguation
Parameters Optimization for Improving ASR Performance in Adverse Real World N...Waqas Tariq
From the existing research it has been observed that many techniques and methodologies are available for performing every step of Automatic Speech Recognition (ASR) system, but the performance (Minimization of Word Error Recognition-WER and Maximization of Word Accuracy Rate- WAR) of the methodology is not dependent on the only technique applied in that method. The research work indicates that, performance mainly depends on the category of the noise, the level of the noise and the variable size of the window, frame, frame overlap etc is considered in the existing methods. The main aim of the work presented in this paper is to use variable size of parameters like window size, frame size and frame overlap percentage to observe the performance of algorithms for various categories of noise with different levels and also train the system for all size of parameters and category of real world noisy environment to improve the performance of the speech recognition system. This paper presents the results of Signal-to-Noise Ratio (SNR) and Accuracy test by applying variable size of parameters. It is observed that, it is really very hard to evaluate test results and decide parameter size for ASR performance improvement for its resultant optimization. Hence, this study further suggests the feasible and optimum parameter size using Fuzzy Inference System (FIS) for enhancing resultant accuracy in adverse real world noisy environmental conditions. This work will be helpful to give discriminative training of ubiquitous ASR system for better Human Computer Interaction (HCI). Keywords: ASR Performance, ASR Parameters Optimization, Multi-Environmental Training, Fuzzy Inference System for ASR, ubiquitous ASR system, Human Computer Interaction (HCI)
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Identification and Control of Three-Links Electrically Driven Robot Arm Using Fuzzy Neural Networks
1. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 14
Identification and Control of Three-Links Electrically Driven
Robot Arm Using Fuzzy Neural Networks
Salam A. Abdulkereem salam_eng@yahoo.com
Department of Computers Engineer
University of Basra
Basra,Iraq
Prof. Dr. Abduladhem A. Ali abduladem1@yahoo.com
Department of Computers Engineer
University of Basra
Basra,Iraq
Abstract
This paper uses a fuzzy neural network (FNN) structure for identifying and controlling nonlinear
dynamic systems such three links robot arm. The equation of motion for three links robot arm
derived using Lagrange’s equation. This equation then combined with the equations of motion for
dc. servo motors which actuated the robot. For the control problem, we present the forward and
inverse adaptive control approaches using the FNN. Computer simulation is performed to view
the results for identification and control.
Keywords: Fuzzy Neural Control, Robot Control, Forward Adaptive Control, Inverse Control, Adaptive
Systems
1. INTRODUCTION
In the past decade, the applications of intelligent control techniques (fuzzy control or neural-
network control) to the motion control of robotic manipulators have received considerable
attention [1], [5]. In general, robotic manipulators have to face various uncertainties in their
dynamics, such as payload parameter, friction, and disturbance. It is difficult to establish an
appropriate mathematical model for the design of a model based control system. Thus, the
general claim of these intelligent control approaches is that they can attenuate the effects of
structured parametric uncertainty and unstructured disturbance by using their powerful learning
ability without a detailed knowledge of the controlled plant in the design processes. Feed forward
neural networks have been shown to obtain successful results in system identification and control
[6]. Such neural networks are static input/output mapping schemes that can approximate a
continuous function to an arbitrary degree of accuracy. Results have also been extended to
recurrent neural networks [7], [9]. For example, Jin et al. [8] studied the approximation of
continuous-time dynamic systems using the dynamic recurrent (DRNN) and a Hopfield-type
DRNN was presented by Funahashi and Nakamura [7]. As is widely known, both fuzzy logic
systems and neural network systems are aimed at exploiting human-like knowledge processing
capability. Moreover, combinations of the two have found extensive applications. This approach
involves merging or fusing fuzzy systems and neural networks into an integrated system to reap
the benefits of both [10]. For instance, Lin and Lee [11] proposed a general neural network model
for a fuzzy logic control and decision system, which is trained to control an unmanned vehicle.
In this paper FNN is used to identify and control a three links robot arm. We present the forward
and inverse identification as offline learning to use the parameters of this stage in control stage.
For control problem, we present the indirect (forward) and direct (inverse) control. Computer
simulation implements to view the results of robot arm application.
2. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 15
This paper is organized as follows. Section II presents the dynamic model of a three-link robot
arm including actuator dynamics briefly [12], [14]. Section III shows the FNN structure. Section IV
FNN identification .Section V presents the FNN control. Section VI presents the simulation results
finally section IX shows the conclusion.
2. Dynamic model of three links Robot arm
Dynamic modeling of a robot manipulator consists of finding the mapping between the forces
exerted on the structures and the joint positions, velocities and accelerations. Two formulations
are mainly used to derive the dynamic model: namely the Lagrange formulation and the Newton-
Euler formulation. A large number of authors and researchers [15], [17], used Lagrange's
approach to drive the general form of robot equation of motion. The Lagrange equations thus
taking on the alternative form [18]:
(1)
FIGURE 1: Three Links Robot Arm
Where , denote the vectors of joint link positions, velocities and acceleration
respectively, I ( ) denotes the inertia matrix, n denote the number of link, P is the
potential energy and denoted the torque of n link. Consider the manipulator of Fig. (1), with
links designed so that their mass centers, C1, C2, and C3, are located at the midpoints of
segments O1O2, O2O3, and O3P, respectively. Moreover, the link has a mass (mn )and a
centroidal moment of inertia in a direction normal to the plane of motion (In ); while the joints are
actuated by motors delivering torques , , and , the lubricant of the joints producing
dissipative torques that we will neglect in this model. Under the assumption that gravity acts in the
direction of Y axis. In general, the dynamic model of armature-controlled DC servo motors which
shown below, on an - link robot manipulator can be expressed in the following form [17]:
(2)
(3)
(4)
Where is the vector of electromagnetic torque, is the diagonal matrix of
X
Y
C3
C2
C1
P
O3
O2
O1
3. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 16
motor torque constants, is the vector of armature currents, is the diagonal
matrix of the moment inertia, is the diagonal matrix of torsional damping
coefficients, denote the vectors of motor shaft positions, velocities, and
accelerations, respectively, is the vector of load torque, is the vector of
armature input voltages, is the diagonal matrix of armature resistance,
is the diagonal matrix of armature inductance, and is the diagonal matrix of the back
electromotive force (EMF) coefficients. In order to apply the dc servo motors for actuating an -
link robot manipulator, a relationship between the joint position and the motor-shaft position
can be represented as follows [17]:
(5)
The governed equation of an n-link robot manipulator including actuator dynamics can be
obtained as [1]:
(6)
Where represents the control effort vector, i.e. armature input voltages,
(7)
(9)
Where is gravity vector, N represents the vector of external disturbance and friction
term . Then we can re-write Eqn. (6) as:
(10)
By using method of numerical integration such Euler method for Eqn. (10) we can get position,
velocity and acceleration for each link.
3. Fuzzy Neural Networks (FNN)
The Architecture of FNN shown in (fig, 2). FNN considered as a special type of neural network
[19], this means special connection and node operation. Every layer and every node have its
practical meaning because the FNN has the structure which is based on both the fuzzy rules and
inference. In the following items each layer shown in (fig, 2) will be described:
1- Input layer
Input layer transmits the input linguistic variables to the output without changed.
2- Hidden layer I
Membership layer represents the input values with the following Gaussian membership
functions [20]:
(8)
4. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 17
(11)
FIGURE 2: Architecture of FNN
Where and (i=1, 2, ... , n ; j=1, 2,.., m), respectively, are the mean and standard deviation
of the Gaussian function in the j
th
term of the i
th
input linguistic variable to the node of this
layer.
3-Hidden layer II
Rule layer implements the fuzzy inference mechanism, and each node in this layer
multiplies the input signals and outputs the result of the product. The output of this layer is
given as [20]:
(12)
Where represent the ith
output of rule layer.
4- Output layer
Layer four is the output layer, and nodes in this layer represent output linguistic variables.
Each node , which computes the output as [20]:
(13)
3.1 Learning Algorithm FNN Identifier
There are three types of parameters in the fuzzy-neural network can be adapted, in the primes
part: the center values and width values of the Gaussian membership functions, whereas,
in the consequence part: the consequence weights values iw . Once the fuzzy-neural network
has been initialized, a gradient decent based back-propagation algorithm is employed to adjust
1
1µ
1
2µ
1
nµ2
1µ
2
2µ
2
nµ
m
1µ
m
m
m m
nµ
m
2µ
1x
2x
nx
2FNy
1w
2w
mw
5. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 18
the parameters of the fuzzy-neural network by using the training patterns. The main goal of
supervised learning algorithm is to minimize the mean square error function [20]:
(14)
Where is the output of is fuzzy-neural network and is the desired output. The gradient
descent algorithm gives the following iterative equations for the parameter values [20]:
(15)
(16)
(17)
Where ࣁ is the learning rate for each parameter in the system, i=1,2…n and j=1,2…m. Taking the
partial derivative of the error function given by Eqn. (14), we can get the following equations:
(18)
(19)
(20)
4. Identification
Two representations are available to identify a dynamical system depending on type of the output
feedback these are parallel model and Series-parallel model [6]. In this paper the series-parallel
identification model is desired. A series-parallel model that is obtained by feeding back the past
values of the plant output (rather than the identifier output) as shown in (Fig,3). This implies that
in this case the identification model has the form [6]:
(21)
The identifier output is represented by and the plant output is denoted by .
5. FNN Control
For system control problems, we focus on the adaptive control of dynamic systems using FNN.
These algorithms denoted as “Fuzzy Neural Model Reference Controller” (FNMRC) in this type of
controllers, back propagation training algorithm is used [16]. There are two distinct approaches
for the FNMRC, the first one result in a direct scheme (inverse control) for the controller and the
second result in an indirect scheme (forward control), the difference between the two may be
shown in figure (4.1) and (4.2).
5.1 Learning Algorithm for Indirect FNN Control (Forward)
Indirect control architecture usually requires an identified system model and the controller design
is based on the learning algorithm. Our goal is to minimize the following cost function:
6. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 19
(22)
Where , and are errors between reference outputs and robot’s link1, link2 and link3
FIGURE 3: Series-Parallel identification model
FIGURE 4.1: Direct FNN model reference learning controller
FIGURE 4.2: Indirect FNN model reference learning controller
Nonlinear
Plant
T
D
L
U(k)
FNN Identifier
Output (yp)
Reference
Model
FNN
Controller Plant
Command
Signal
Σ
+
-
ec
u
yr
7. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 20
output respectively, then the gradient of error with respect to weights , mean and standard
deviation of the Gaussian function are given:
(23)
The identifier can provide the system sensitivity and it can be computed by the chain rule:
(26)
Where , are l
th
output of FNN controller, O
th
output of robot plant respectively and where:
5.2 Learning Algorithm for Direct FNN Control (Inverse)
The FNN inverse control is shown in the (fig, 5), in which two FNN are present, one for the
inverse identification and the other for controller. The basic structure of the inverse controller
consists of the controller network only, which is the same to the identifier network in the offline
learning. The simple concept of the inverse controller is the controller block that represents the
inverse transfer function of the robot plant, so the product result of the two blocks (robot plant and
(24)
(25)
8. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 21
controller) must equal unity. Hence the output of the robot plant will be equal to desired input of
the controller.
FIGURE 5: FNN inverse control
6. SIMULATION RESULTS
In the following examples two methods of control presented in above sections are implemented
by FNN for three links robot arm. The simulation carried by MATLABT software. The no. of rules
and outputs are 50 and 3 respectively, in each method of control. The initial mean and standard
of membership function were computed as Eqns. (27) and (28) [21], beside the 0.001values for
weights. Following two examples are viewed. The most important parameters that affect the
control performance of the robotic system are the external disturbance , the friction term
, and the parameter variation of 3
rd
link’s mass . In all two example simulation, three
circumstances including the:
1- Nominal situation ( kg and N=0) at beginning.
2- Parameter variation situation occurring at t=15 sec ( kg).
3- Disturbance in addition, friction forces are also considered in this simulation.
Hence,
(27)
(28)
Where , are the predetermined maximal and minimal bounds of nth
input to FNN.
6.1 Example 1
In this example the forward control is implemented by FNN in each one the forward identifier is
used to calculate the plant sensitivity, the initial parameters of identifier will take from final values
proceed in the offline learning. The eighteen inputs are fed to FNN controller, the learning rate of
weights, mean and standard are , and respectively . figures
(6.a) to (6.f) are shown the FNN forward control position response and mean square error for
link1, link2 and link3 respectively for 100 epochs.
9. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 22
FIGURE 6: FNN forward control simulation results of position response and mean square error for Link1,
Link2 and Link3 (a)-(f)
10. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 23
FIGURE 7: FNN inverse control simulation results of position response and mean square error for Link1,
Link2 and Link3 (a)-(f)
11. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 24
6.2 Example 2
The FNN inverse control presented in this example, the structure of controller same the structure
of the inverse identifier which only changes the input to inverse identifier by reference
input to inverse controller. Inverse identifier used here so that the parameters
generated in offline learning considered initial parameters to online inverse identifier and inverse
controller. The eighteen inputs are fed to FNN controller, the learning rate of weights, mean and
standard are , and respectively. Figures (7.a) to (7.f)
are shown the FNN inverse control position response and mean square error for link1, link2 and
link3 respectively for 100 epochs.
7. CONCLUSION
In this paper use FNN for identification and control for dynamic nonlinear systems such three
links robot arm. From the previous examples we conclude that the FNN is powerful for identify
and control nonlinear system, in example1 use indirect control with online forward identification
and the gradient in mean square error is done and in example2 use the direct control technique
with online inverse identification after use the parameters are get from offline inverse identification
to use in online work. Table (1) shows the gradient mean square error for both examples for each
link and the mean square error for each link when we applied the traditional PD control
(Proportion and Derivative control) on them in order to compare the values of MSE among
example1, example2 (they applied by FNN control) and PD control, the main difference between
FNN control and traditional PD control is a PD control can’t adapt its gains (kp, kd) when some
disturbance insert to plant in otherwise the FNN control can adapt its parameters (wc, mcij and scij)
by online learning algorithm.
For future work the control technique by FNN without identification will study to reduce load of
computation.
TABLE 1: Mean square error
8. REFERENCES
[1] Rong-jong Wa and Po-Chen Chen,“Robust Neural-Fuzzy-Network Control for Robot
Manipulator Including Actuator Dynamics”, IEEE Trans. Indst. Elect. vol. 53, no. 4, Aug.
2006.
[2] S. J. Huang and J. S. Lee, “A stable self-organizing fuzzy controller for robotic motion
control,” IEEE Trans. Ind. Electron., vol. 47, no. 2, pp. 421–428, Apr. 2000.
[3] B. K. Yoo and W. C. Ham, “Adaptive control of robot manipulator using fuzzy compensator,”
IEEE Trans. Fuzzy Syst., vol. 8, no. 2, pp. 186–199, Apr. 2000.
Example Link1 Link2 Link3
1 0.0093 0.0093 0.0085
2 0.018 0.0181 0.0125
PD control 0.0095 0.009 0.0098
12. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 25
[4] Y. C. Chang, “Neural network-based H-infinite tracking control for robotic systems,” Proc.
Inst. Electr . Eng.—Control Theory Appl., vol. 147, no. 3, pp. 303–311, May 2000.
[5] Y. H. Kim and F. L. Lewis, “Optimal design of CMAC neural-network controller for robot
manipulators,” IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 30, no. 1, pp. 22–31, Feb.
2000.
[6] K. S. Narendra and K. Parthasarathy, “Identification and control of dynamical system using
neural networks,” IEEE Trans. Neural Networks, vol. 1, pp. 4–27, Jan. 1990.
[7] K. Funahashi and Y. Nakamura, Approximation of dynamical systems by continuous-time
recurrent neural network,” Neural Networks, vol.6, pp. 801–806, 1993.
[8] L. Jin, P. N. Nikiforuk, and M. Gupta, “Approximation of discrete-time state-space trajectories
using dynamic recurrent neural networks,” IEEE Trans. Automat. Contr., vol. 40, pp. 1266–
1270, July 1995.
[9] C. C. Ku and K. Y. Lee, “Diagonal recurrent neural networks for dynamic systems control,”
IEEE Trans. Neural Networks, vol. 6, pp.144–156, Jan. 1995.
[10] Ching-Hung Lee and Ching-Cheng Teng, “Identification and Control of Dynamic Systems
Using Recurrent Fuzzy Neural Networks”, IEEE Trans. Fuzzy system, vol. 8, no. 4, Aug.
2000
[11] C. T. Lin and C. S. G. Lee, “Neural-network-based fuzzy logic control and decision system,”
IEEE Trans. Computer. , vol. 40, pp. 1320–1336, Dec. 1991.
[12] B. S. Chen, H. J. Uang, and C. S. Tseng, “Robust tracking enhancement of robot systems
including motor dynamics: A fuzzy-based dynamic game approach,” IEEE Trans. Fuzzy
Syst., vol. 6, no. 4, pp. 538–552,Nov. 1998.
[13] C. Ishii, T. Shen, and K. Tamura, “Robust model following control for a robot manipulator,”
Proc. Inst. Electr. Eng.—Control Theory Appl., vol. 144, no. 1, pp. 53–60, Jan. 1997.
[14] R. J. Schilling, Fundamentals of Robotics: Analysis and Control. Hoboken, NJ: Prentice-Hall,
1998.
[15] Mark W.Spong, Seth H., M. Vidyasagar, “Robot Modeling and Control”, John Wiley and
Sons, INC., 2001
[16] Abdul Baqi, J.N., "Neuro-Fuzzy Control of robot Arm" MSC. Thesis, University of Basrah,
College of Engineering, Feb. 2004.
[17] Rong-Jong Wai, P. C. Chen, Chun-Yen Tu, “Robust Neural-fuzzy-network Control for
Rigid-link Electrically Driven Robot Manipulator”, IEEE Trans. Ind. Electron., 30th
annual
conference, pp. 1328–1349, Nov. 2004.
[18] Jorge Angels, ”Fundamentals of robotic mechanical systems: theory, methods and
Algorithms”, Springer, 2003.
[19] C. T. Leondes, "Fuzzy logic and expert systems applications", Academic Press, 1998.
[20] Rong-Jong Wai, Chia-Chin Chu," Robust Petri Fuzzy-Neural-Network Control for Linear
Induction Motor Drive", IEEE trans. on Ind. Elect. , Vol. 54, No. 1, pp. 177-189, Feb. 2007.
13. Salam A. Abdulkereem & Prof.Dr.Abduladhem A. Ali
International Journal of Robotics and Automation (IJRA), Volume (2) : Issue (1) : 2011 26
[21] Rong-Jong Wai, Chia-Ming Liu," Design of Dynamic Petri Recurrent Fuzzy Neural Network
and Its Application to Path-Tracking Control of Nonholonomic Mobile Robot", IEEE
transactions on Ind. Elec., Vol. 56, NO. 7, pp.2667-2683, July 2009.