A hybrid bacterial foraging and modified particle swarm optimization for mode...IJECEIAES
This paper study the model reduction procedures used for the reduction of large-scale dynamic models into a smaller one through some sort of differential and algebraic equations. A confirmed relevance between these two models exists, and it shows same characteristics under study. These reduction procedures are generally utilized for mitigating computational complexity, facilitating system analysis, and thence reducing time and costs. This paper comes out with a study showing the impact of the consolidation between the Bacterial-Foraging (BF) and Modified particle swarm optimization (MPSO) for the reduced order model (ROM). The proposed hybrid algorithm (BF-MPSO) is comprehensively compared with the BF and MPSO algorithms; a comparison is also made with selected existing techniques.
Model reduction of unstable systems based on balanced truncation algorithm IJECEIAES
Model reduction of a system is an approximation of a higher-order system to a lower-order system while the dynamic behavior of the system is almost unchanged. In this paper, we will discuss model order reduction (MOR) strategies for unstable systems, in which the method based on the balanced truncation algorithm will be focused on. Since each MOR algorithm has its strengths and weakness, practical applications should be suitable for each specific requirement. Simulation results will demonstrate the correctness of the algorithms.
In recent times, fractional order controllers are gaining more interest. There are several fractional order controllers are available in literature. Still, tuning of these controllers is one of the main issues which the control community is facing. In this paper, online tuning of five dierent fractional order controllers is discussed viz. tilted proportional-integral-derivative (T-PID) controller, fractional order proportional-integral (FO-PI) controller, fractional order proportional-derivative (FO-PD) controller, fractional order proportional-integral-derivative (FO-PID) controller. A reference tracking method is proposed for tuning of fractional order controllers. First order with dead time (FOWDT) system is used to check feasibility of the control strategy.
A hybrid bacterial foraging and modified particle swarm optimization for mode...IJECEIAES
This paper study the model reduction procedures used for the reduction of large-scale dynamic models into a smaller one through some sort of differential and algebraic equations. A confirmed relevance between these two models exists, and it shows same characteristics under study. These reduction procedures are generally utilized for mitigating computational complexity, facilitating system analysis, and thence reducing time and costs. This paper comes out with a study showing the impact of the consolidation between the Bacterial-Foraging (BF) and Modified particle swarm optimization (MPSO) for the reduced order model (ROM). The proposed hybrid algorithm (BF-MPSO) is comprehensively compared with the BF and MPSO algorithms; a comparison is also made with selected existing techniques.
Model reduction of unstable systems based on balanced truncation algorithm IJECEIAES
Model reduction of a system is an approximation of a higher-order system to a lower-order system while the dynamic behavior of the system is almost unchanged. In this paper, we will discuss model order reduction (MOR) strategies for unstable systems, in which the method based on the balanced truncation algorithm will be focused on. Since each MOR algorithm has its strengths and weakness, practical applications should be suitable for each specific requirement. Simulation results will demonstrate the correctness of the algorithms.
In recent times, fractional order controllers are gaining more interest. There are several fractional order controllers are available in literature. Still, tuning of these controllers is one of the main issues which the control community is facing. In this paper, online tuning of five dierent fractional order controllers is discussed viz. tilted proportional-integral-derivative (T-PID) controller, fractional order proportional-integral (FO-PI) controller, fractional order proportional-derivative (FO-PD) controller, fractional order proportional-integral-derivative (FO-PID) controller. A reference tracking method is proposed for tuning of fractional order controllers. First order with dead time (FOWDT) system is used to check feasibility of the control strategy.
Robust design of a 2 dof gmv controller a direct self-tuning and fuzzy schedu...ISA Interchange
This paper presents a study on self-tuning control strategies with generalized minimum variance control in a fixed two degree of freedom structure–or simply GMV2DOF–within two adaptive perspectives. One, from the process model point of view, using a recursive least squares estimator algorithm for direct self-tuning design, and another, using a Mamdani fuzzy GMV2DOF parameters scheduling technique based on analytical and physical interpretations from robustness analysis of the system. Both strategies are assessed by simulation and real plants experimentation environments composed of a damped pendulum and an under development wind tunnel from the Department of Automation and Systems of the Federal University of Santa Catarina.
Matlab Implementation of Baseline JPEG Image Compression Using Hardware Optim...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
—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.
Design of predictive controller for smooth set point tracking for fast dynami...eSAT Journals
Abstract Model Predictive Control is generally used for slow dynamic system. Here efforts are made to implement MPC controller for Fast dynamic System. Speed control of DC motor is taken as fast dynamic system for which the MPC controller would be implemented. To control the speed of the DC motor Generalized Predictive Control (GPC) algorithm is used. In this paper, ARIX model based GPC control is implemented in 2-DOF structure. Transfer function of the DC motor is derived using LABVIEW and system identification tool of MATLAB. From the response of the system, it can be seen that the GPC has improved the performance of the system rather than PID control algorithm from disturbance rejection point of view. Keywords: MPC (Model Predictive Controller), GPC (Generalized Predictive Controller), ARIX Model (Auto Regressive Integrated Exogenous Model).
An Improved Adaptive Multi-Objective Particle Swarm Optimization for Disassem...IJRESJOURNAL
With the development of productivity and the fast growth of the economy, environmental pollution, resource utilization and low product recovery rate have emerged subsequently, so more and more attention has been paid to the recycling and reuse of products. However, since the complexity of disassembly line balancing problem (DLBP) increases with the number of parts in the product, finding the optimal balance is computationally intensive. In order to improve the computational ability of particle swarm optimization (PSO) algorithm in solving DLBP, this paper proposed an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm. Firstly, the evolution factor parameter is introduced to judge the state of evolution using the idea of fuzzy classification and then the feedback information from evolutionary environment is served in adjusting inertia weight, acceleration coefficients dynamically. Finally, a dimensional learning strategy based on information entropy is used in which each learning object is uncertain. The results from testing in using series of instances with different size verify the effect of proposed algorithm.
APPLICATION OF D-K ITERATION TECHNIQUE BASED ON H∞ ROBUST CONTROL THEORY FOR ...cscpconf
The D-K iteration method of controller design combines H∞ synthesis that ensure robustness
and µ-analysis that takes care of parametric uncertainties, and yields a good performance of
the robust controller. The idea is basically to find a controller that minimizes the peak value
over frequency of the upper bound on µ. This robust control technique is applied for the
Power System Stabilizer design for a Single Machine Infinite Bus (SMIB) system, which has
already proved to be a successful tool in mitigating low frequency oscillations caused by
small disturbances and for improving damping characteristic of a power system. Robust
control toolbox of MATLAB has been used for the design. The effectiveness of the proposed PSS for wide range of operating conditions has been shown for the SMIB system with the help of simulation with MATLAB.
Genetic Algorithm for solving Dynamic Supply Chain Problem AI Publications
The solution of dynamic supply chain problem is studied using both genetic algorithms and multistage dynamic programming. This is possible by employing Euler approximation method to approximate the differential of the variables. The problem is reformulated as unconstrained optimization problem which solved by genetic Algorithm and Multi Stages Dynamic Programming. The solution evaluation results from using dynamic programming and genetic algorithm is performed
Justification of Montgomery Modular Reductionacijjournal
one of the most known and widely used methods in Cryptography is the method suggested by Peter
Montgomery; this method is based on the changing of the original reduction modulo by some other
convenient modulo, the original Montgomery paper gives the algorithm without any considerations
leading to that algorithm.
Single Machine Power Network Load Frequency Control Using T-S Fuzzy Based Rob...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.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Theoretical work submitted to the Journal should be original in its motivation or modeling structure. Empirical analysis should be based on a theoretical framework and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors.
The International Journal of Engineering & Science would take much care in making your article published without much delay with your kind cooperation
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
Optimal PID Controller Design for Speed Control of a Separately Excited DC Mo...ijscmcj
This paper presents a new approach to determine the optimal proportional-integral-derivative controller parameters for the speed control of a separately excited DC motor using firefly optimization technique. Firefly algorithm is one of the recent evolutionary methods which are inspired by the Firefly’s behavior in nature. The firefly optimization technique is successfully implemented using MATLAB software. A comparison is drawn from the results obtained between the linear quadratic regulator and firefly optimization techniques. Simulation results are presented to illustrate the performance and validity of the design method.
A simplified method of designing a phase lead compensator to improve the m-s-...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.
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.
Design of GCSC Stabilizing Controller for Damping Low Frequency OscillationsIJAEMSJORNAL
This paper presents a systematic procedure for modeling and simulation of a power system equipped with FACTS type Gate Controlled Series Compensator (GCSC) based stabilizer controller. Single Machine Infinite Bus (SMIB) power system was investigated for evaluation of GCSC stabilizing controller for enhancing the overall dynamic system performance. PSO algorithm is employed to compute the optimal parameters of damping controller. Eigenvalues of system under various operating condition and nonlinear time domain simulation is employed to verify the effectiveness and robustness of GCSC stabilizing controller in damping low frequency oscillations (LFO) modes.
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...ijscmcj
This paper presents a new approach to determine the optimal proportional-integral-derivative controller
parameters for the speed control of a separately excited DC motor using firefly optimization technique.
Firefly algorithm is one of the recent evolutionary methods which are inspired by the Firefly’s behavior in
nature. The firefly optimization technique is successfully implemented using MATLAB software. A
comparison is drawn from the results obtained between the linear quadratic regulator and firefly
optimization techniques. Simulation results are presented to illustrate the performance and validity of the
design method.
Robust design of a 2 dof gmv controller a direct self-tuning and fuzzy schedu...ISA Interchange
This paper presents a study on self-tuning control strategies with generalized minimum variance control in a fixed two degree of freedom structure–or simply GMV2DOF–within two adaptive perspectives. One, from the process model point of view, using a recursive least squares estimator algorithm for direct self-tuning design, and another, using a Mamdani fuzzy GMV2DOF parameters scheduling technique based on analytical and physical interpretations from robustness analysis of the system. Both strategies are assessed by simulation and real plants experimentation environments composed of a damped pendulum and an under development wind tunnel from the Department of Automation and Systems of the Federal University of Santa Catarina.
Matlab Implementation of Baseline JPEG Image Compression Using Hardware Optim...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
—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.
Design of predictive controller for smooth set point tracking for fast dynami...eSAT Journals
Abstract Model Predictive Control is generally used for slow dynamic system. Here efforts are made to implement MPC controller for Fast dynamic System. Speed control of DC motor is taken as fast dynamic system for which the MPC controller would be implemented. To control the speed of the DC motor Generalized Predictive Control (GPC) algorithm is used. In this paper, ARIX model based GPC control is implemented in 2-DOF structure. Transfer function of the DC motor is derived using LABVIEW and system identification tool of MATLAB. From the response of the system, it can be seen that the GPC has improved the performance of the system rather than PID control algorithm from disturbance rejection point of view. Keywords: MPC (Model Predictive Controller), GPC (Generalized Predictive Controller), ARIX Model (Auto Regressive Integrated Exogenous Model).
An Improved Adaptive Multi-Objective Particle Swarm Optimization for Disassem...IJRESJOURNAL
With the development of productivity and the fast growth of the economy, environmental pollution, resource utilization and low product recovery rate have emerged subsequently, so more and more attention has been paid to the recycling and reuse of products. However, since the complexity of disassembly line balancing problem (DLBP) increases with the number of parts in the product, finding the optimal balance is computationally intensive. In order to improve the computational ability of particle swarm optimization (PSO) algorithm in solving DLBP, this paper proposed an improved adaptive multi-objective particle swarm optimization (IAMOPSO) algorithm. Firstly, the evolution factor parameter is introduced to judge the state of evolution using the idea of fuzzy classification and then the feedback information from evolutionary environment is served in adjusting inertia weight, acceleration coefficients dynamically. Finally, a dimensional learning strategy based on information entropy is used in which each learning object is uncertain. The results from testing in using series of instances with different size verify the effect of proposed algorithm.
APPLICATION OF D-K ITERATION TECHNIQUE BASED ON H∞ ROBUST CONTROL THEORY FOR ...cscpconf
The D-K iteration method of controller design combines H∞ synthesis that ensure robustness
and µ-analysis that takes care of parametric uncertainties, and yields a good performance of
the robust controller. The idea is basically to find a controller that minimizes the peak value
over frequency of the upper bound on µ. This robust control technique is applied for the
Power System Stabilizer design for a Single Machine Infinite Bus (SMIB) system, which has
already proved to be a successful tool in mitigating low frequency oscillations caused by
small disturbances and for improving damping characteristic of a power system. Robust
control toolbox of MATLAB has been used for the design. The effectiveness of the proposed PSS for wide range of operating conditions has been shown for the SMIB system with the help of simulation with MATLAB.
Genetic Algorithm for solving Dynamic Supply Chain Problem AI Publications
The solution of dynamic supply chain problem is studied using both genetic algorithms and multistage dynamic programming. This is possible by employing Euler approximation method to approximate the differential of the variables. The problem is reformulated as unconstrained optimization problem which solved by genetic Algorithm and Multi Stages Dynamic Programming. The solution evaluation results from using dynamic programming and genetic algorithm is performed
Justification of Montgomery Modular Reductionacijjournal
one of the most known and widely used methods in Cryptography is the method suggested by Peter
Montgomery; this method is based on the changing of the original reduction modulo by some other
convenient modulo, the original Montgomery paper gives the algorithm without any considerations
leading to that algorithm.
Single Machine Power Network Load Frequency Control Using T-S Fuzzy Based Rob...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.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
Theoretical work submitted to the Journal should be original in its motivation or modeling structure. Empirical analysis should be based on a theoretical framework and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors.
The International Journal of Engineering & Science would take much care in making your article published without much delay with your kind cooperation
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
Optimal PID Controller Design for Speed Control of a Separately Excited DC Mo...ijscmcj
This paper presents a new approach to determine the optimal proportional-integral-derivative controller parameters for the speed control of a separately excited DC motor using firefly optimization technique. Firefly algorithm is one of the recent evolutionary methods which are inspired by the Firefly’s behavior in nature. The firefly optimization technique is successfully implemented using MATLAB software. A comparison is drawn from the results obtained between the linear quadratic regulator and firefly optimization techniques. Simulation results are presented to illustrate the performance and validity of the design method.
A simplified method of designing a phase lead compensator to improve the m-s-...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.
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.
Design of GCSC Stabilizing Controller for Damping Low Frequency OscillationsIJAEMSJORNAL
This paper presents a systematic procedure for modeling and simulation of a power system equipped with FACTS type Gate Controlled Series Compensator (GCSC) based stabilizer controller. Single Machine Infinite Bus (SMIB) power system was investigated for evaluation of GCSC stabilizing controller for enhancing the overall dynamic system performance. PSO algorithm is employed to compute the optimal parameters of damping controller. Eigenvalues of system under various operating condition and nonlinear time domain simulation is employed to verify the effectiveness and robustness of GCSC stabilizing controller in damping low frequency oscillations (LFO) modes.
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...ijscmcj
This paper presents a new approach to determine the optimal proportional-integral-derivative controller
parameters for the speed control of a separately excited DC motor using firefly optimization technique.
Firefly algorithm is one of the recent evolutionary methods which are inspired by the Firefly’s behavior in
nature. The firefly optimization technique is successfully implemented using MATLAB software. A
comparison is drawn from the results obtained between the linear quadratic regulator and firefly
optimization techniques. Simulation results are presented to illustrate the performance and validity of the
design method.
OPTIMAL PID CONTROLLER DESIGN FOR SPEED CONTROL OF A SEPARATELY EXCITED DC MO...ijscmcjournal
This paper presents a new approach to determine the optimal proportional-integral-derivative controller
parameters for the speed control of a separately excited DC motor using firefly optimization technique.
Firefly algorithm is one of the recent evolutionary methods which are inspired by the Firefly’s behavior in
nature. The firefly optimization technique is successfully implemented using MATLAB software. A
comparison is drawn from the results obtained between the linear quadratic regulator and firefly
optimization techniques. Simulation results are presented to illustrate the performance and validity of the
design method.
Advanced Stability Analysis of Control Systems with Variable Parametersjournal ijrtem
The purpose of the current research is to advance further the D-Partitioning method and
emphasize on its practical application. It has the objective to clarify it in a user friendly manner in order to
simplify its implementation. By applying the basic initial ideas of the method, the main line of the research is the
development of a generalized stability analysis tool and demonstrating its application. With the aid of this tool,
proper parameter values can be chosen for a desirable performance and stability of a system. The analysis tool
can be practically used when one, two or more system’s parameters are varied independently or simultaneously.
Basically this tool defines regions of stability in the space of the system’s parameters.
Advanced Stability Analysis of Control Systems with Variable ParametersIJRTEMJOURNAL
The purpose of the current research is to advance further the D-Partitioning method and
emphasize on its practical application. It has the objective to clarify it in a user friendly manner in order to
simplify its implementation. By applying the basic initial ideas of the method, the main line of the research is the
development of a generalized stability analysis tool and demonstrating its application. With the aid of this tool,
proper parameter values can be chosen for a desirable performance and stability of a system. The analysis tool
can be practically used when one, two or more system’s parameters are varied independently or simultaneously.
Basically this tool defines regions of stability in the space of the system’s parameters.
In this study the controller for three tank multi loop system is designed using coefficient Diagram
method. Coefficient Diagram Method is one of the polynomial methods in control design. The
controller designed by using CDM technique is based on the coefficients of the characteristics
polynomial of the closed loop system according to the convenient performance such as equivalent
time constant, stability indices and stability limit. Controller is designed for the three tank process
by using CDM Techniques; the simulation results show that the proposed control strategies have
good set point tracking and better response capability.
International Journal of Engineering Inventions (IJEI) provides a multidisciplinary passage for researchers, managers, professionals, practitioners and students around the globe to publish high quality, peer-reviewed articles on all theoretical and empirical aspects of Engineering and Science.
The peer-reviewed International Journal of Engineering Inventions (IJEI) is started with a mission to encourage contribution to research in Science and Technology. Encourage and motivate researchers in challenging areas of Sciences and Technology.
COUPLED FPGA/ASIC IMPLEMENTATION OF ELLIPTIC CURVE CRYPTO-PROCESSORIJNSA Journal
In this paper, we propose an elliptic curve key generation processor over GF(2163) scheme based on the Montgomery scalar multiplication algorithm. The new architecture is performed using polynomial basis. The Finite Field operations use a cellular automata multiplier and Fermat algorithm for inversion. For real time implementation, the architecture has been tested on an ISE 9.1 Software using Xilinx Virtex II Pro FPGA and on an ASIC CMOS 45 nm technology as well. The proposed implementation provides a time of 2.07 ms and 38 percent of Slices in Xilinx Virtex II Pro FPGA. Such features reveal the high efficiently of this implementation design.
Design of Multiloop Controller for Three Tank Process Using CDM Techniques ijsc
In this study the controller for three tank multi loop system is designed using coefficient Diagram method. Coefficient Diagram Method is one of the polynomial methods in control design. The controller designed by using CDM technique is based on the coefficients of the characteristics polynomial of the closed loop system according to the convenient performance such as equivalent time constant, stability indices and stability limit. Controller is designed for the three tank process by using CDM Techniques; the simulation results show that the proposed control strategies have good set point tracking and better response capability.
A Novel Hybrid Approach for Stability Analysis of SMIB using GA and PSOINFOGAIN PUBLICATION
Stability exploration has drawn more attention in contemporary research for huge interconnected power system. It is a complex frame to describe the behaviour of system, hence it can create an overhead for modern computer to analyse the power system stability (PSS).The preliminary design and optimization can be achieved by low order liner model. This paper presents a hybrid approach for the stability analysis of single machine infinite bus system using generic power system stabilizer (GPSS) and proportional-integral-derivative.
Operation cost reduction in unit commitment problem using improved quantum bi...IJECEIAES
Unit Commitment (UC) is a nonlinear mixed integer-programming problem. UC used to minimize the operational cost of the generation units in a power system by scheduling some of generators in ON state and the other generators in OFF state according to the total power outputs of generation units, load demand and the constraints of power system. This paper proposes an Improved Quantum Binary Particle Swarm Optimization (IQBPSO) algorithm. The tests have been made on a 10-units simulation system and the results show the improvement in an operation cost reduction after using the proposed algorithm compared with the ordinary Quantum Binary Particle Swarm Optimization (QBPSO) algorithm
FPGA IMPLEMENTATION OF SOFT OUTPUT VITERBI ALGORITHM USING MEMORYLESS HYBRID ...VLSICS Design
The importance of convolutional codes is well established. They are widely used to encode digital data before transmission through noisy or error-prone communication channels to reduce occurrence of errors and memory. This paper presents novel decoding technique, memoryless Hybrid Register Exchange with simulation and FPGA implementation results. It requires single register as compared to Register Exchange Method (REM) & Hybrid Register Exchange Method (HREM); therefore the data trans-fer operations and ultimately the switching activity will get reduced.
Matlab codes for Sizing and Calculating the Aircraft Stability & PerformanceAhmed Momtaz Hosny, PhD
Matlab codes for Sizing and Calculating the Aircraft Stability & Performance, with the knowledge of the DATCOM Results. (Simple and rapid way to analyze and evaluate the aircraft performance)
Inferring the Optimum UAV's Trajectories Configuration Over Definite Intruder...Ahmed Momtaz Hosny, PhD
Inferring the Optimum UAV's Trajectories Configuration Over Definite Intruder Paths with Multiple Random Starting Points Via Genetic Algorithm - Taking into consideration a set of synchronized UAV's - (Provided with the relevant Matlab Code).
Development of Fuzzy Logic LQR Control Integration for Full Mission Multistag...Ahmed Momtaz Hosny, PhD
This work investigates the performance on the aircraft control system during air refuel purposes of the Linear Quadratic Regulator (LQR) control alone, and the integration between fuzzy control and LQR. LQR is modern linear control that is suitable for multivariable state feedback and is known to yield good performance for linear systems or for nonlinear systems where the nonlinear aspects are presented. The fuzzy control is known to have the ability to deal with nonlinearities without having to use advanced mathematics. The LQR integrated fuzzy control (LQRIFC) simultaneously makes use of the good performance of the LQR in the region close to switching curve, and the effectiveness of the fuzzy control in region away from switching curve. A new analysis of the fuzzy system behavior presented helps to make possible precise integration of LQR features into the fuzzy control. The LQRIFC is verified by simulation to suppress the uncertain instability more effectively than the LQR alone besides minimizing the time of the mission proposed. The aerial refueling process has been divided into 3 basic stages (initial stability stage, tracking stage, alignment stage) to meet all the process requirements and constraints with minimizing the whole mission time period. GA has been used to tune the fuzzy logic controller parameters and some PID’s. The control strategy was applied to both aerial refueling methods. And the MATLAB simulation results show the validity and the efficiency of using the proposed control approach.
Development of Fuzzy Logic LQR Control Integration for Full Mission Multistag...Ahmed Momtaz Hosny, PhD
This work investigates the performance on the aircraft control system during air refuel purposes of the Linear Quadratic Regulator (LQR) control alone, and the integration between fuzzy control and LQR. LQR is modern linear control that is suitable for multivariable state feedback and is known to yield good performance for linear systems or for nonlinear systems where the nonlinear aspects are presented. The fuzzy control is known to have the ability to deal with nonlinearities without having to use advanced mathematics. The LQR integrated fuzzy control (LQRIFC) simultaneously makes use of the good performance of the LQR in the region close to switching curve, and the effectiveness of the fuzzy control in region away from switching curve. A new analysis of the fuzzy system behavior presented helps to make possible precise integration of LQR features into the fuzzy control. The LQRIFC is verified by simulation to suppress the uncertain instability more effectively than the LQR alone besides minimizing the time of the mission proposed. The aerial refueling process has been divided into 3 basic stages (initial stability stage, tracking stage, alignment stage) to meet all the process requirements and constraints with minimizing the whole mission time period. GA has been used to tune the fuzzy logic controller parameters and some PID’s. The control strategy was applied to both aerial refueling methods. And the MATLAB simulation results show the validity and the efficiency of using the proposed control approach.
DEVELOPMENT OF A NEUROFUZZY CONTROL SYSTEM FOR THE GUIDANCE OF AIR ...Ahmed Momtaz Hosny, PhD
ABSTRACT
In recent years, there has been an increasing interest in the fusion of neural networks and fuzzy logic specially in missile control problems. A technique for the preliminary design of a control system is presented using a neurofuzzy approach for a highly nonlinear MIMO 5_DOF AIM 9R model. The model reflects cross coupling effects between the longitudinal and lateral motions. Two neural network controllers are used for the low level control of each motion separately. The control effort of these networks is then blended by a fuzzy logic controller to obtain the overall control action.The fuzzy controller which is a Mamdani type inference system has 25 rule base designed to cope with model uncertainties specially in cross coupling between lateral and longitudinal motions. A computer simulation is performed to compare between various control techniques. The result showed the effectiveness of the hybrid system compared to other control strategies where fuzzy systems or neural networks are used separately.
DEVELOPMENT OF NEUROFUZZY CONTROL SYSTEM FOR THE GUIDANCE OF AIR TO AIR MISS...Ahmed Momtaz Hosny, PhD
ABSTRACT
In recent years, there has been an increasing interest in the fusion of neural networks and fuzzy logic specially in missile control problems. A technique for the preliminary design of a control system is presented using a neurofuzzy approach for a highly nonlinear MIMO 5_DOF AIM 9R model. The model reflects cross coupling effects between the longitudinal and lateral motions. Two neural network controllers are used for the low level control of each motion separately. The control effort of these networks is then blended by a fuzzy logic controller to obtain the overall control action.The fuzzy controller which is a Mamdani type inference system has 25 rule base designed to cope with model uncertainties specially in cross coupling between lateral and longitudinal motions. A computer simulation is performed to compare between various control techniques. The result showed the effectiveness of the hybrid system compared to other control strategies where fuzzy systems or neural networks are used separately.
A Comparison Study between Inferred State-Space and Neural Network Based Syst...Ahmed Momtaz Hosny, PhD
In this paper, system identifications of an unmanned aerial vehicle (UAV) based on inferred state space and multiple neural networks were presented. In this work an optimization approach was used to conclude an inferred state space and the multiple neural networks system identifications based on the genetic algorithms separately. The UAV is a multi-input multi-output (MIMO) nonlinear system. Models for such MIMO system are expected to be adaptive to dynamic behavior and robust to environment.
Development of a Customized Autopilot for Unmanned Helicopter Model Using Gen...Ahmed Momtaz Hosny, PhD
The objective of this paper is to develop a customized autopilot system that enables a helicopter model to carry out an autonomous flight using on-board microcontroller. The main goal of this project is to provide a comprehensive controller design methodology, Modeling, simulation, guidance and verification for an unmanned helicopter model. The autopilot system was designed to demonstrate autonomous maneuvers such as flying over the planned waypoints with constant forward speed.
A Comparison Study between Inferred State-Space and Neural Network Based Syst...Ahmed Momtaz Hosny, PhD
Abstract:
In this paper, system identifications of an unmanned aerial vehicle (UAV) based on inferred state space and multiple neural networks were presented. In this work an optimization approach was used to conclude an inferred state space and the multiple neural networks system identifications based on the genetic algorithms separately.
The presented work is focusing on an inferred state space based system identification which is a new approach seldom used, but it is also easier and more stable compared with the multi-network based system identification during the modeling of dynamic behavior of nonlinear systems.
The objective of this paper is to develop a customized autopilot system that enables a helicopter model to carry out an autonomous flight using on-board microcontroller. The main goal of this project is to provide a comprehensive controller design methodology, Modeling, simulation, guidance and verification for an unmanned helicopter model. The autopilot system was designed to demonstrate autonomous maneuvers such as flying over the planned waypoints with constant forward speed and considerable steep maneuvers. For the controller design, the nonlinear dynamic model of the Remote Control helicopter was built by employing Lumped Parameter approach comprising of four different subsystems such as actuator dynamics, rotary wing dynamics, force and moment generation process and rigid body dynamics. The nonlinear helicopter mathematical model was then linearized using small perturbation theory for stability analysis and linear feedback control system design. The linear state feedback for the stabilization and control of the helicopter was derived using Pole Placement Method. The overall dynamic system control with output feedback was computed using Genetic Algorithm. Series of Matlab-Simulink models and guidance algorithms were presented in this work to simulate and verify the autopilot system performance. The proposed autopilot has shown acceptable capability of stabilizing and controlling the helicopter during tracking the desired waypoints. This paper is presenting a detailed comparison study for two different guidance strategies. The first strategy is concerning the difference between the desired heading or elevation referred to the next waypoint and the actual heading or elevation of the unmanned helicopter model. The second strategy is concerning the relative distance between the actual and the desired trajectories. In other words the first method is tracking the waypoints while the second one is tracking the trajectory. In this work a comparison study was conducted through the mentioned strategies simulation to show the significant differences in the output performance. Some performance indexes were presented to evaluate the system performance errors and the control effort needed for both strategies using the same desired trajectory and the same waypoints.
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FUZZY LOGIC CONTROLLER TUNNING VIA ADAPTIVE GENETIC ALGORITHM APPLIED TO AIRCRAFT LONGITUDINAL MOTION
1. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 1
Military Technical College
Kobry El-Kobba
Cairo, Egypt
12-th International Conference
on
Aerospace Sciences &
Aviation Technology
FUZZY LOGIC CONTROLLER TUNNING VIA ADAPTIVE GENETIC
ALGORITHM APPLIED TO AIRCRAFT LONGITUDINAL MOTION
Ahmed Momtaz*, Han Chao**
ABSTRACT
Design of an efficient fuzzy logic controller involves the optimization of
parameters of fuzzy sets, denormalized gains and proper choice of rule base.
There are several techniques reported in recent literature that use genetic
algorithms to learn and optimize a fuzzy logic controller. This paper develops
methodologies to learn and optimize fuzzy logic controller parameters based on
genetic algorithm. The strategies developed have been applied to control
integration between LQR and nonlinear Fuzzy PID of F16 aircraft pitch motion
control and fuzzy controller developed with the help of iterative learning from
operator experience. The results show that Genetic-Fuzzy approaches were able
to learn rule base and identify membership function parameters accurately.
KEY WORDS
Intelligent control, Fuzzy logic, Genetic algorithm, Linear quadratic regulator
*PHD Candidate, School of astronautics, Beihang University, Beijing, China
**Professor, School of astronautics, Beihang University, Beijing, China
2. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 2
1. INTRODUCTION
GA uses a direct analogy of natural behavior (Fig. 1), They work with a
population of individuals, each reprinting a possible solution to a given problem.
Each individual is assigned a fitness score according to how good its solution to
the problem is. The highly fit individuals are given opportunities to reproduce, by
cross breeding with other individuals in the population. This produces new
individuals as offspring, who share some features taken from each parent. The
least fit members of the population are less likely to get selected for reproduction,
and will eventually die out. Adaptive GAs whose parameters, such as the
population, size, cross over probability and mutation probability are varied during
the GA is running thus converging to the optimum solution faster.
2. APPLICATION OF GA FUNCTIONS FOR TUNING FUZZY PID
CONTROLLER PARAMETERS
As shown in the following figure Fig. 2, the fuzzy PID controller consists of output
denormalized gains, input-output membership functions and rule bases, [1], [2].
The main objective of the pre-explained GA procedure is to optimize (minimize)
the output performance index (maximize fitness function) of the whole integrated
control system used in the pitch control motion of F-16 aircraft. Application of GA
MATLAB code combined with SIMULINK control model is implemented to
minimize the performance index as explained later [3].
Using GA to minimize the value of the output performance index:
∫
∞
=
0
2
)_( dtsimpitcheJ (1)
Where e(pitch_sim) is the pitch angle error to workspace. The previous index
can be obtained from the nonlinear simulation of the pitch control model
consequently GA can use it as the fitness function.
2.1 Optimizing Fuzzy Output Gains
2.1.1 Using binary system coding
Coding:using 10-bit binary genes to express . Table 1 shows the
upper and lower gain limits. For example (KP) from bit 1 , to bit
10 is . Then string to 30-bit binary cluster.
DIP KKK ,,
(0)0000000000
(1023)1111111111 DIP KKK ,,
000010001011101110000000110111:x express a gene,the former 10-bit
express KP, the second portion express KI and the third one express the KD .
3. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 3
Decoding:Cut one string of 30-bit binary string to three 10-bit binary
string,then converts them to decimal system values: y1, y2 and y3. Table 2 shows
the decoding equations.
2.1.2 Evaluation of fitness function
Fitness function is the main criterion of the GA algorithm, as it represents how
much the system is optimum and stable. The following equation describes the
relation between the fitness function and the performance index.
1
))_((),,( −
= simpitchJKKKf DIP (2)
2.1.3 Design operators
Proportion selection operator,single point crossover operator,basic bit
mutation operator.
2.1.4 Parameters of GA
Population size is , generation02=M 03=G , crossover probability
,mutation probability0.60c =P 0.10m =P 。
Adopting the above steps, after 100 steps iteration, we get the best individuals
When KP=7.190, KD =2.958 and KI= -2.870 the output performance index has the
minimum value,that is 0.9785 shown in Fig. 3.
2.2 Tuning of Fuzzy Sets
It is presented a universal algorithm for solving a very general class of
optimization problems applied to fuzzy sets. From studying how such a GA can
be applied to the optimization of fuzzy sets. An appropriate coding, genetic
operators (in case that the standard variants are not sufficient), and a fitness
measure is presented [3], [4].
2.2.1 Coding fuzzy subsets of an interval
A reasonable resolution for encoding the membership degrees is n = 8. Such an
8-bit coding is used in several software systems, too. For most problems,
however, simpler representations of fuzzy sets are sufficient. Many real-world
applications use triangular and trapezoidal membership functions Fig. 4.
Not really surprising, a triangular fuzzy set can be encoded as
where δ is an upper boundary for the size of the offsets, for example δ = (b −
a)/2. The same can be done analogously for trapezoidal fuzzy sets:
4. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 4
In specific control applications, where the smoothness of the control surface
plays an important role, fuzzy sets of higher differentiability must be used. The
most prominent representative is the bell-shaped fuzzy set whose membership
function is given by a Gaussian bell function:
2
2
2
)(
)( u
rx
ex
−
−
=μ (3)
The “bell-shaped analogue” to trapezoidal fuzzy sets are so-called radial basis
functions:
q
q
rx
rx
if
if
ex u
qrx
≤
≥
−
−
⎪
⎩
⎪
⎨
⎧
=
−−
−
1
)(
2
2
2
)(
μ (4)
Fig. 5 shows a typical bell-shaped membership function. Again the coding
method is straightforward, i.e.
where ε is a lower limit for the spread u. Analogously for radial basis functions:
The final step is simple and obvious, In order to define a coding of the whole
configuration, i.e. of all fuzzy sets involved, it is sufficient to put coding of all
relevant fuzzy sets into one large string. This type of membership functions were
used in describing the fuzzy PID controller denormalized gains ( ) as it
has better representation of system uncertainty.
DIP KKK ,,
2.2.2 Coding whole fuzzy partitions
In this work a simple example of an increasing sequence of trapezoidal-triangular
fuzzy sets has been presented. Such a “fuzzy partition” is uniquely determined by
an increasing sequence of 2N points, where N is the number of linguistic values
we consider. The mathematical formulation is the following:
],[
],[
0
1
)( 21
10
12
2
1 xx
xx
x
x
otherwise
if
if
xx
xx
x ∈
∈
⎪
⎪
⎩
⎪⎪
⎨
⎧
−
−
=μ
(5)
12
],[
],[
],[
0
1)(
122
1222
2232
122
2
3222
32
−≤≤
∈
∈
∈
⎪
⎪
⎪
⎩
⎪
⎪
⎪
⎨
⎧
−
−
−
−
=
−
−−
−−
−
−−
−
Nifor
xxx
xxx
xxx
otherwise
if
if
if
xx
xx
xx
xx
x
ii
ii
ii
ii
i
ii
i
iμ
(6)
5. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 5
22
2232
3222
32
],[
0
1)( −
−−
−−
−
≥
∈
⎪
⎪
⎩
⎪
⎪
⎨
⎧
−
−
= N
NN
NN
N
N x
xx
x
x
otherwise
if
ifxx
xx
xμ
(7)
Fig. 6 shows a typical example with N = 3 that was used to represent (error,
error change) in the proposed fuzzy PID controller. It is not wise to encode
the values xi as they are, since this requires constraints for ensuring that xi
are non-decreasing. A good alternative is to encode the offsets:
2.2.3 Genetic operators
Since this GA can only deal with binary representations of fuzzy sets and
partitions, all the GA operators that mentioned before are also applicable
here. However, that the offset encoding of fuzzy partitions is highly epistemic.
More specifically, if the first bit encoding x1 is changed, the whole partition is
shifted. If this results in bad convergence, the crossover operator should be
modified. A suggestion can be found in [5]. Fig. 6 shows an example what
happens if two fuzzy partitions are crossed with normal one-point crossover.
Fig. 7 shows the same for bitwise mutation.
2.2.4 Rescaling process (Decoding of all fuzzy partitions)
Using the following simple equation to normalize the membership variables
(error, error change) by:
1020/)10202( −×= yx
Therefore the optimum (normalized) membership functions can be obtained
for both (error, error change). The following figures (Fig. 8a, Fig. 8b, Fig. 8c,
Fig. 8d, Fig. 8e) illustrate the optimum input-output membership functions that
obtained from the adaptive genetic algorithm for 40 samples and 20
generations at some operating point of (250 ft/s speed and 1000 ft altitude).
2.3 Rule Base Weight Optimization
The genetic algorithm has been applied to 100 samples of input-output
simulation data obtained from fuzzy PID controller. The rules obtained by the
algorithm are shown below. The values in parentheses after each rule
represent the firing strength of the corresponding rule.
1. if (e is NB) and (ec is NB) then (kp is PB)(Ki is NB)(Kd is PS)(.5811)
: : : : : : : : : :
49. if (e is PB) and (ec is PB) then (kp is NB)(Ki is PB)(Kd is PB)(.3121)
6. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 6
2. THE LQR INTEGRATED FUZZY CONTROL (LQRIFC)
The LQR integrated fuzzy control utilizes both advantages from the LQR
controller and fuzzy logic controller as LQR controller can easily satisfies the
flying qualities and pilot rating requirements and fuzzy control can cope with the
nonlinearity of the system introducing a smart way to modify the output gains
according to the actual performance blending the dynamic response that
generating better performance than using LQR alone [6], [7]. Fig. 9 describes the
LQR integrated fuzzy control (LQRIFC) for pitch controller.
The states and outputs of the plant plus the compensator are:
⎥
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎢
⎣
⎡
=
ε
α
δ
α
F
e
q
x ,
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎣
⎡
=
ε
α
qy
F
System dynamics is described by the following state space through LQR design
algorithm at several trimmed points for pitch control; Table 3 shows the linearized
matrices of F-16 model at different operating points (different altitudes). The LQR
closed loop system poles satisfy the flying qualities specifications [8] such as the
damping ratio and the natural frequencies. The tuned fuzzy logic controller copes
with the LQR output error thus enhancing the net output system performance.
Membership functions could be sliding back and forth so that it suppress low
frequencies disturbance on the other hand the low pass filter introduced will cope
with high frequencies noise that produce a robust and optimal control system, as
the integrated control system utilizes both advantages of the LQR and FLC
techniques (optimal and robust design). Fig.10 shows the difference between
both cases with the optimized fuzzy controller and without fuzzy controller as the
additional FLC enhances the performance index (PI) more than 8.5%. Table 4
shows the different optimized LQRIFC gains at different altitude. The following
linear equations describe the dynamics of the longitudinal motion of the aircraft at
velocity 250 (ft/s).
x.
=Ax + Bu + Gr (8)
y=Cx + Fr (9)
z=Hx (10)
7. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 7
⎥
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎢
⎣
⎡
−
−
−=
0002958.570
010000.10
002.2000
00
~~~
00
~~~
eqqqq
eq
BAA
BAA
A
δα
αδααα
, ,
⎥
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎢
⎣
⎡
=
0
0
2.20
0
0
B
⎥
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎢
⎣
⎡
=
1
0
0
0
0
G
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎣
⎡
=
0
0
0
F
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎣
⎡
=
10000
0002958.570
02958.57000
C
, [ ]0002958.570=H , [ ]lq KKKKyu α−=−=
3. APPLICATION METHODOLOGY
Applying the integrated control system of the previous technique on the F-16
nonlinear model during descending slope phase during the landing process with
input of °−= 5.2dθ , with applying DRYDEN vertical gust model, therefore verifying
the output performance with applicable flying qualities [4] that results in satisfied
performance for the fuzzy PID controller. Fig. 11 and Fig. 12 illustrate the whole
system control effort and the fuzzy controller contribution output to the elevator
actuator. Fig. 13 and Fig. 14 illustrate the output performances of the integrated
control system with optimized fuzzy PID controller such as the altitude
descending rate and the descending angle. It is clear now from these figures that
the combination of both LQR and fuzzy logic produces stable and robust control
system.
5. CONCLUSION
In this paper an optimization technique (GA) was presented to tune fuzzy logic
controller parameters. A new MATLAB code was used to perform the GA
operations for the proposed application. The optimized output parameters from
the GA algorithm were used to tune the fuzzy logic controller in order to achieve
robust and stable output performance of the aircraft control system (longitudinal
motion). Moreover the proposed integration utilizes both advantages of LQR and
fuzzy PID controller such as the verification of the flying qualities issues and
introducing variable gains that can cope with the different uncertainty during the
actual flight regimes according to the nature of flexible fuzzy controller output
gains. Besides introducing such nonlinear fuzzy PID controller makes up some of
the disadvantages of using linear controller (LQR) with aircraft nonlinear
modeling such as pre-calculated constant gain matrix at each operating points.
8. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 8
REFERENCES
[1] Zadeh, L. A, “Fuzzy Sets”, Information and Control, Vol. 8, 1965, pp. 338-353.
[2] Takagi, T. and Sugeno, M., “Fuzzy Identification of Systems and its
Application to Modeling and Control”, IEEE Transactions on Systems, Man and
Cybernetics, Vol. 15, 1985.
[3] Goldberg, D., Genetic Algorithms in Search, Optimization & Machine
Learning, Addison Wesley Longman, Inc.,1989.
[4] Teo, L.S., Bin Khalid, M., and Yusof, R., “Tuning of a Neuro-Fuzzy Controller
by Genetic Algorithm”, IEEE Transactions on Systems, Man and Cybernetics,
Part B, Vol. 29, Issue 2, 1999, pp. 226 -236
[5] Mamdani, E.H. and Assilian, A., “An Experiment in Linguistic Synthesis with a
Fuzzy Logic Controller”, International Journal of Man Machine Studies, Vol. 7,
No. 1, 1975, pp. 1-13.
[6] Stevens, B. L., Lewis, F.L., & Al-Sunni, F. (1991). Aircraft flight controls design
using output feedback. Journal of Guidance, Control, and Dynamics
[7] Stevens, B. L., Lewis, F.L. (1992). Aircraft Control And Simulation. New York:
John Wiley & Sons, Inc.
[8] Flying Qualities of Piloted Airplanes, MIL-F-8785C, 5 Nov. 1980.
Fig. 1. The flow of GA functions and process
9. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 9
Fig. 2. Nonlinear fuzzy PID controller
Fig.3. Objective function J and Fitness function F
Fig. 4. Triangular and trapezoidal membership functions
Fig. 5. Bell-shaped membership functions
10. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 10
Fig.6. Example for one-point crossover of fuzzy partitions
Fig. 7. Mutating a fuzzy partitions
Fig. 8a Input variable “error”
Fig. 8b Input variable “error change”
11. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 11
Fig. 8c Output variable “Kp”
Fig. 8d Output variable “Ki”
Fig. 8e Output variable “Kd”
Fig. 9. LQR integrated fuzzy control (LQRIFC) for pitch controller
12. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 12
Fig. 10. Integrated system step response in both cases with optimized fuzzy
controller and without fuzzy controller
Fig. 11. Total elevator angle (deg) Fig.12. Fuzzy controller contribution output
(deg)
Fig. 13. Descending angel (deg) Fig. 14. Descending altitude (ft)
Table 1 Gain Limits
Denormalized
Gain
Minimum
limit
Maximum
limit
KP 1 10
KD -.1 -2.5
KI .05 1.8
Table 2 Decoding Equation
Denormalized gains Decoding equation
KP
1
1023
9 1
+×
y
13. Proceeding of the 12-th ASAT Conference, 29-31 May 2007 GUD-03 13
KD
1.
1023
4.2 2
−×−
y
KI
05.
1023
75.1 3
+×
y
Table 3 Linearized Matrices
Alt
(ft)
ααA
~
qAα
~
eBαδ
~
αqA
~
qqA
~
eqB δ
~
1000 -0.8972 0.9502 -0.0019 -3.6241 -1.2147 -0.2650
1500 -0.8325 0.9533 -0.0017 -3.3307 -1.1265 -0.2438
2000 -0.7716 0.9562 -0.0017 -3.0570 -1.0433 -0.2235
Table 4 Gain values
Alt
(ft) 1000 1500 2000
αK 0.2086 0.2104 0.2127
qK -0.7971 -0.8157 -0.9091
iK 4.6106 4.5618 5.0274
pK 7.190 8.8725 8.1053
DK 2.958 2.754 2.333
IK -2.870 -2.650 -2.230