In this paper, a robust controller for a Six Degrees of Freedom (6 DOF) coaxial trirotor helicopt... more In this paper, a robust controller for a Six Degrees of Freedom (6 DOF) coaxial trirotor helicopter control is proposed in presence of defects in the system. A control strategy based on the coupling of the interval type-2 fuzzy logic control and sliding mode control technique are used to design a controller. The main purpose of this work is to eliminate the chattering phenomenon and guaranteeing the stability and the robustness of the system. In order to achieve this goal, interval type-2 fuzzy logic control has been used to generate the discontinuous control signal. The simulation results have shown that the proposed control strategy can greatly alleviate the chattering effect, and perform good reference tracking in presence of defects in the system.
In this paper, a Fault-Tolerant control of 2 DOF Helicopter (TRMS System) Based on H-infinity is ... more In this paper, a Fault-Tolerant control of 2 DOF Helicopter (TRMS System) Based on H-infinity is presented. In particular, the introductory part of the paper presents a Fault-Tolerant Control (FTC), the first part of this paper presents a description of the mathematical model of TRMS, and the last part of the paper presented and a polytypic Unknown Input Observer (UIO) is synthesized using equalities and LMIs. This UIO is used to observe the faults and then compensate them, in this part the shown how to design a fault-tolerant control strategy for this particular class of non-linear systems.
In this paper we present a new design method for the fight control of an autonomous quadrotor hel... more In this paper we present a new design method for the fight control of an autonomous quadrotor helicopter based on fuzzy sliding mode control using backstepping approach. Due to the underactuated property of the quadrotor helicopter, the controller can move three positions (x,y,z) of the helicopter and the yaw angle to their desired values and stabilize the pitch and roll angles. A first-order nonlinear sliding surface is obtained using the backstepping technique, on which the developed sliding mode controller is based. Mathematical development for the stability and convergence of the system is presented. The main purpose is to eliminate the chattering phenomenon. Thus we have used a fuzzy logic control to generate the hitting control signal. The performances of the nonlinear control method are evaluated by simulation and the results demonstrate the effectiveness of the proposed control strategy for the quadrotor helicopter in vertical flights.
ABSTRACT The helicopter dynamic includes nonlinearities, parametric uncertainties and is subject ... more ABSTRACT The helicopter dynamic includes nonlinearities, parametric uncertainties and is subject to unknown external disturbances. Such complicated dynamics involve designing sophisticated control algorithms that can deal with these difficulties. In this paper, a type 2 fuzzy logic PID controller is proposed for TRMS (twin rotor mimo system) control problem. Using triangular membership functions and based on a human operator experience, two controllers are designed to control the position of the yaw and the pitch angles of the TRMS. Simulation results are given to illustrate the effectiveness of the proposed control scheme.
Transactions of the Institute of Measurement and Control, 2014
ABSTRACT In this paper, a new approach for the implementation of non-linear predictive control is... more ABSTRACT In this paper, a new approach for the implementation of non-linear predictive control is proposed using fuzzy modelling and the artificial bee colony (ABC) algorithm. The main difficulty relevant to the implementation of non-linear predictive control techniques is obtaining, in real time, accurate solutions to the optimization problem. The aim of this work is to derive a simple and efficient algorithm that can solve the non-linear optimization problem with minimal computational time; this allows the real-time feasibility of the control algorithm to be ensured. Indeed, to deal with the problem of slow and premature convergence of the ABC algorithm, a new enhanced version of this algorithm is proposed. In this version, to improve the convergence speed, the initial population is generated using a chaotic map and a modified update equation is used. Furthermore, to avoid the premature convergence of the ABC algorithm, a new expression for the limit parameter, which allows an increase in the exploratory capabilities of the algorithm, is proposed. The modified ABC algorithm allows accurate solutions for the optimization problem of non-linear predictive control with low computational burden to be obtained. First, a statistical analysis of the convergence of the ABC improved version, using some well-known benchmark functions, is presented and compared with that of other ABC algorithm versions. Then, to assess the efficiency and the performance of the proposed control algorithm, control of a continuous stirred tank rector model is considered. To demonstrate further the effectiveness of the proposed controller, a comparative study, using several meta-heuristic algorithms, is carried out.
2013 8th International Conference on Electrical and Electronics Engineering (ELECO), 2013
ABSTRACT The control of the quadrotor helicopter includes nonlinearities, uncertainties and exter... more ABSTRACT The control of the quadrotor helicopter includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. This paper presents a control strategy for an underactuated six degrees of freedom (6 DOF) quadorotor helicopter, based on the sliding mode control (SMC). The main purpose of this work is to proposed a non linear observer based on extended kalman filter (EKF) to estimate the unmeasured states. Finally simulation results are included to indicate the quadrotor UAV with the proposed controller ensure a good tracking of a desired trajectory and remain robust to the external disturbances.
ABSTRACT In this work, a modified particle swarm optimization (PSO) algorithm is proposed to solv... more ABSTRACT In this work, a modified particle swarm optimization (PSO) algorithm is proposed to solve the optimization problem of fuzzy predictive control. The main objective is to obtain an efficient control algorithm with a low computational burden and a good control performance. This is done essentially by reducing both the PSO population and the number of iterations needed for each sampling time. The control accuracy and computational efficiency of the proposed algorithm are illustrated by considering the control of the continuous stirred tank reactor.
2010 17th IEEE International Conference on Electronics, Circuits and Systems, 2010
The predictive control has currently become a precious tool in various domains. It is largely stu... more The predictive control has currently become a precious tool in various domains. It is largely studied and well known in the case of linear systems. An extension of this technique for nonlinear systems control has recently been the subject of many works. Several algorithms and particularly those using fuzzy logic and neural networks have been proposed. In this work a non linear predictive control method that uses a neural model is presented. It allows the analytical determination of the control law. The main objective of this work is the application of this method to the control of a robotic manipulator.
2009 35th Annual Conference of IEEE Industrial Electronics, 2009
The predictive control of nonlinear systems has recently been the subject of several research wor... more The predictive control of nonlinear systems has recently been the subject of several research works and several algorithms, in particular those using fuzzy logic and neural networks. In this paper, we present a method for unconstrained predictive control of nonlinear systems. This method, uses a static neural network as a prediction model and is based on the idea of dividing
ABSTRACT In this work a fuzzy model-based predictive control (FMPC) method that uses modified par... more ABSTRACT In this work a fuzzy model-based predictive control (FMPC) method that uses modified particle swarm optimization (PSO) is presented. The main objective of this work is the application of this method to the control of a Selective Compliant Assembly Robot Arm (SCARA) with four degrees of freedom (4-DOF).
Mots clés : systèmes non linéaires, identification, réseaux de neurones. Résumé -dans la dernière... more Mots clés : systèmes non linéaires, identification, réseaux de neurones. Résumé -dans la dernière décennie, plusieurs travaux de recherche ont montré l'efficacité de l'application des réseaux de neurones à l'identification et au contrôle des systèmes non linéaires. Dans ce travail nous considérons le problème de l'identification des systèmes non linéaires en présence des perturbations. Les différents types des perturbations sont considérés comme étant la réponse libre d'un système linéaire ou non linéaire. L'objectif est de construire un modèle pour le système à identifier, de telle façon à rejeter ces perturbations. Des justifications théoriques pour la solution proposée ont été données, ensuite cette solution est validée par des exemples de simulation.
In this paper, a robust controller for a Six Degrees of Freedom (6 DOF) coaxial trirotor helicopt... more In this paper, a robust controller for a Six Degrees of Freedom (6 DOF) coaxial trirotor helicopter control is proposed in presence of defects in the system. A control strategy based on the coupling of the interval type-2 fuzzy logic control and sliding mode control technique are used to design a controller. The main purpose of this work is to eliminate the chattering phenomenon and guaranteeing the stability and the robustness of the system. In order to achieve this goal, interval type-2 fuzzy logic control has been used to generate the discontinuous control signal. The simulation results have shown that the proposed control strategy can greatly alleviate the chattering effect, and perform good reference tracking in presence of defects in the system.
In this paper, a Fault-Tolerant control of 2 DOF Helicopter (TRMS System) Based on H-infinity is ... more In this paper, a Fault-Tolerant control of 2 DOF Helicopter (TRMS System) Based on H-infinity is presented. In particular, the introductory part of the paper presents a Fault-Tolerant Control (FTC), the first part of this paper presents a description of the mathematical model of TRMS, and the last part of the paper presented and a polytypic Unknown Input Observer (UIO) is synthesized using equalities and LMIs. This UIO is used to observe the faults and then compensate them, in this part the shown how to design a fault-tolerant control strategy for this particular class of non-linear systems.
In this paper we present a new design method for the fight control of an autonomous quadrotor hel... more In this paper we present a new design method for the fight control of an autonomous quadrotor helicopter based on fuzzy sliding mode control using backstepping approach. Due to the underactuated property of the quadrotor helicopter, the controller can move three positions (x,y,z) of the helicopter and the yaw angle to their desired values and stabilize the pitch and roll angles. A first-order nonlinear sliding surface is obtained using the backstepping technique, on which the developed sliding mode controller is based. Mathematical development for the stability and convergence of the system is presented. The main purpose is to eliminate the chattering phenomenon. Thus we have used a fuzzy logic control to generate the hitting control signal. The performances of the nonlinear control method are evaluated by simulation and the results demonstrate the effectiveness of the proposed control strategy for the quadrotor helicopter in vertical flights.
ABSTRACT The helicopter dynamic includes nonlinearities, parametric uncertainties and is subject ... more ABSTRACT The helicopter dynamic includes nonlinearities, parametric uncertainties and is subject to unknown external disturbances. Such complicated dynamics involve designing sophisticated control algorithms that can deal with these difficulties. In this paper, a type 2 fuzzy logic PID controller is proposed for TRMS (twin rotor mimo system) control problem. Using triangular membership functions and based on a human operator experience, two controllers are designed to control the position of the yaw and the pitch angles of the TRMS. Simulation results are given to illustrate the effectiveness of the proposed control scheme.
Transactions of the Institute of Measurement and Control, 2014
ABSTRACT In this paper, a new approach for the implementation of non-linear predictive control is... more ABSTRACT In this paper, a new approach for the implementation of non-linear predictive control is proposed using fuzzy modelling and the artificial bee colony (ABC) algorithm. The main difficulty relevant to the implementation of non-linear predictive control techniques is obtaining, in real time, accurate solutions to the optimization problem. The aim of this work is to derive a simple and efficient algorithm that can solve the non-linear optimization problem with minimal computational time; this allows the real-time feasibility of the control algorithm to be ensured. Indeed, to deal with the problem of slow and premature convergence of the ABC algorithm, a new enhanced version of this algorithm is proposed. In this version, to improve the convergence speed, the initial population is generated using a chaotic map and a modified update equation is used. Furthermore, to avoid the premature convergence of the ABC algorithm, a new expression for the limit parameter, which allows an increase in the exploratory capabilities of the algorithm, is proposed. The modified ABC algorithm allows accurate solutions for the optimization problem of non-linear predictive control with low computational burden to be obtained. First, a statistical analysis of the convergence of the ABC improved version, using some well-known benchmark functions, is presented and compared with that of other ABC algorithm versions. Then, to assess the efficiency and the performance of the proposed control algorithm, control of a continuous stirred tank rector model is considered. To demonstrate further the effectiveness of the proposed controller, a comparative study, using several meta-heuristic algorithms, is carried out.
2013 8th International Conference on Electrical and Electronics Engineering (ELECO), 2013
ABSTRACT The control of the quadrotor helicopter includes nonlinearities, uncertainties and exter... more ABSTRACT The control of the quadrotor helicopter includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. This paper presents a control strategy for an underactuated six degrees of freedom (6 DOF) quadorotor helicopter, based on the sliding mode control (SMC). The main purpose of this work is to proposed a non linear observer based on extended kalman filter (EKF) to estimate the unmeasured states. Finally simulation results are included to indicate the quadrotor UAV with the proposed controller ensure a good tracking of a desired trajectory and remain robust to the external disturbances.
ABSTRACT In this work, a modified particle swarm optimization (PSO) algorithm is proposed to solv... more ABSTRACT In this work, a modified particle swarm optimization (PSO) algorithm is proposed to solve the optimization problem of fuzzy predictive control. The main objective is to obtain an efficient control algorithm with a low computational burden and a good control performance. This is done essentially by reducing both the PSO population and the number of iterations needed for each sampling time. The control accuracy and computational efficiency of the proposed algorithm are illustrated by considering the control of the continuous stirred tank reactor.
2010 17th IEEE International Conference on Electronics, Circuits and Systems, 2010
The predictive control has currently become a precious tool in various domains. It is largely stu... more The predictive control has currently become a precious tool in various domains. It is largely studied and well known in the case of linear systems. An extension of this technique for nonlinear systems control has recently been the subject of many works. Several algorithms and particularly those using fuzzy logic and neural networks have been proposed. In this work a non linear predictive control method that uses a neural model is presented. It allows the analytical determination of the control law. The main objective of this work is the application of this method to the control of a robotic manipulator.
2009 35th Annual Conference of IEEE Industrial Electronics, 2009
The predictive control of nonlinear systems has recently been the subject of several research wor... more The predictive control of nonlinear systems has recently been the subject of several research works and several algorithms, in particular those using fuzzy logic and neural networks. In this paper, we present a method for unconstrained predictive control of nonlinear systems. This method, uses a static neural network as a prediction model and is based on the idea of dividing
ABSTRACT In this work a fuzzy model-based predictive control (FMPC) method that uses modified par... more ABSTRACT In this work a fuzzy model-based predictive control (FMPC) method that uses modified particle swarm optimization (PSO) is presented. The main objective of this work is the application of this method to the control of a Selective Compliant Assembly Robot Arm (SCARA) with four degrees of freedom (4-DOF).
Mots clés : systèmes non linéaires, identification, réseaux de neurones. Résumé -dans la dernière... more Mots clés : systèmes non linéaires, identification, réseaux de neurones. Résumé -dans la dernière décennie, plusieurs travaux de recherche ont montré l'efficacité de l'application des réseaux de neurones à l'identification et au contrôle des systèmes non linéaires. Dans ce travail nous considérons le problème de l'identification des systèmes non linéaires en présence des perturbations. Les différents types des perturbations sont considérés comme étant la réponse libre d'un système linéaire ou non linéaire. L'objectif est de construire un modèle pour le système à identifier, de telle façon à rejeter ces perturbations. Des justifications théoriques pour la solution proposée ont été données, ensuite cette solution est validée par des exemples de simulation.
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