3rd International Conference on Systems and Control, 2013
In this paper, we present a new tuning method for a PID controller of a nonlinear system. The pro... more In this paper, we present a new tuning method for a PID controller of a nonlinear system. The proposed approach is an hybridization of the Artificial Bees Colony (ABC) and the Predator and prey (P\&P) behavior. The employed bees will explore new sources in the search space while running away from their predators. Simulations of the proposed algorithm are carried out over an inverted pendulum nonlinear system. Obtained performances are better then Genetic algorithm when compared in the same conditions.
International Journal of Intelligent Systems and Applications, Oct 8, 2014
In this paper an enhanced approach based on a modified biogeography optimization with predator an... more In this paper an enhanced approach based on a modified biogeography optimization with predator and prey behavior (PMBBO) is presented. The approach uses several predators with new proposed prey's movement formula. The potential of using a modified predator and prey model is to increase the diversification along the optimization process so to avoid local optima and reach the optimal solution quickly. The proposed approach is used in tuning the gains of PID controller for nonlinear systems (Mass spring damper and an inverted pendulum) and has given remarkable results when compared to genetic algorithm and classical BBO.
International Journal of Intelligent Systems and Applications, Aug 8, 2014
In this paper, we present a combination of sequential trained radial basis function networks and ... more In this paper, we present a combination of sequential trained radial basis function networks and fuzzy techniques to enhance the variable structure controllers dedicated to robotics systems. In this aim, four RBFs networks were used to estimate the model based part parameters (Inertia, Centrifugal and Coriolis, Gravity and Friction matrices) of a variable structure controller so to respond to model variation and disturbances, a sequential online training algorithm based on Growing-Pruning "GAP" strategy and Kalman filter was implemented. To eliminate the chattering effect, the corrective control of the VS control was computed by a fuzzy controller. Simulations are carried out to control three degrees of freedom SCARA robot manipulator where the obtained results show good disturbance rejection and chattering elimination.
This paper deals with the application of a variable structure observer developed for a class of n... more This paper deals with the application of a variable structure observer developed for a class of nonlinear systems to solve the trajectory tracking problem for rigid robot manipulators. The analyzed approach to observer design proposes a simple design methodology for systems having completely observable linear parts and bounded nonlinearities and/or uncertainties. This observer is basically the conventional Luenberger observer with an additional switching term that is used to guarantee robustness against modeling errors and system uncertainties. To solve the tracking problem, we use a control law developed for robot manipulators in the full information case. The closed loop system is shown to be globally asymptotically stable based on Lyapunov arguments. Simulation results on a 3-DOF robot manipulator show the asymptotic convergence of the vectors of observation and tracking errors.
Technological Advances in microelectronic and telecommunication fields enable the existence of ti... more Technological Advances in microelectronic and telecommunication fields enable the existence of tiny computing units, very small and more efficient. In the context of these new technologies, Wireless Sensor Networks (WSN) have emerged. The main research objective in WSN domain is the development of algorithms and protocols ensuring minimal energy consumption. Most proposed solutions are based on one-layer stack model approach. Recently, other works tend to exploit together many layers in order to optimize energy consumption. In this paper, we propose a Cross-Layer Medium Access Control (CL-MAC) protocol using two adjacent layers (MAC and Network) to economize energy for WSN. The basic idea behind our protocol is to wake-up only nodes belonging to a routing path from the source to the base station (Sink) by exploiting routing information while other nodes leave maintained as long time as possible in a sleep mode. The protocol is modeled using a time Petri net and validated by TiNA tool. The simulation results demonstrate the effectiveness of our proposal in terms of energy consumption and latency.
The present paper is dedicated to the presentation and implementation of an optimized technique a... more The present paper is dedicated to the presentation and implementation of an optimized technique allowing an on-line estimation of a robot manipulator parameters to use them in a computed torque control. Indeed the proposed control law needs the exact robot model to give good performances. The complexity of the robot manipulator and its strong non-linearity makes it hard to know its parameters. Therefore, we propose in this paper to use neuro-fuzzy networks Sequential Adaptive Fuzzy Inference System (SAFIS) to estimate the parameters of the controlled robot manipulator.
2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), 2012
The aim of this work is the combination of radial basis function networks (RBF) and fuzzy techniq... more The aim of this work is the combination of radial basis function networks (RBF) and fuzzy techniques to enhance the sliding mode controllers. In fact, three RBFs networks were used to estimate the model parameters and to respond to model variation and disturbances, a sequential training algorithm based on Kalman filter was implemented, and to eliminate the chattering effect, a fuzzy controller was designed. The hybrid sliding mode controller had shown a strong ability to get over noise and uncertainties. The former controller was used to control a two degree of freedom robot manipulator.
2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), 2012
Abstract: A sliding mode control has been a great interest in the control engineering community, ... more Abstract: A sliding mode control has been a great interest in the control engineering community, with many applications particularly in the robot manipulators control. This paper presents investigations into the development of Sliding Mode control approach based ...
International Journal of Intelligent Systems and Applications, 2014
In this paper, we present a combination of sequential trained radial basis function networks and ... more In this paper, we present a combination of sequential trained radial basis function networks and fuzzy techniques to enhance the variable structure controllers dedicated to robotics systems. In this aim, four RBFs networks were used to estimate the model based part parameters (Inertia, Centrifugal and Coriolis, Gravity and Friction matrices) of a variable structure controller so to respond to model variation and disturbances, a sequential online training algorithm based on Growing-Pruning "GAP" strategy and Kalman filter was implemented. To eliminate the chattering effect, the corrective control of the VS control was computed by a fuzzy controller. Simulations are carried out to control three degrees of freedom SCARA robot manipulator where the obtained results show good disturbance rejection and chattering elimination.
2013 IEEE International Conference on Industrial Technology (ICIT), 2013
ABSTRACT In this paper, we try to present a sliding mode with fuzzy-neural network controller for... more ABSTRACT In this paper, we try to present a sliding mode with fuzzy-neural network controller for nonlinear systems. It is a special nonlinear control method (SMC) which has quick response, insensitive to parameters variation and disturbance. Online identification for plants is not needed, it's very suitable for nonlinear system control, but in reality using the chattering reduction and elimination are key problem in SMC. By using a function-augmented sliding hyper plane, it is guaranteed that the output tracking error converges to zero in finite time which can be set arbitrarily. The fuzzy-neural network mainly Self Tuning Fuzzy Inference System (STFIS) is used to approximate the unknown system functions and switch item. Finally, the sliding-mode with fuzzy-neural network control is used to control single inverted pendulum and confirms the validity of the proposals. Results of simulations containing tests of robustness are presented and realized in MATLAB environment.
2012 IEEE International Symposium on Industrial Electronics, 2012
A robust control approach denoted sliding control of MIMO nonlinear system based on the output fe... more A robust control approach denoted sliding control of MIMO nonlinear system based on the output feedback linearization is developed to attenuate the parametric uncertainties. The scheme is dedicated to model of unmanned aerial vehicles (the quadrotor UAV). We assume that the model of the plant is not precise, due to nondeterministic knowledge of inertias parameters. Tracking control is used to stabilize the equilibrium of the system, while all the state supposed to be measurable. The analysis is based on tracking errors during transients and at the steady state, on performance, stability and robustness with respect to plant uncertainties. Simulation results are carried out.
2012 IEEE International Conference on Complex Systems (ICCS), 2012
This paper is dedicated to present the newly developed evolutionary algorithm: Biogeography based... more This paper is dedicated to present the newly developed evolutionary algorithm: Biogeography based optimization (BBO). It is based on the migration of information between habitats like in Biogeography. The BBO is then used to tune a PID controller of nonlinear systems where the parameters are optimized. Simulations of the proposed algorithm are carried out over an inverted pendulum and second on mass-spring damper system. Performances of the BBO are compared to those of genetic algorithm in PID tuning problem and the BBO gives acceptable results even best then GA.
3rd International Conference on Systems and Control, 2013
In this paper, we present a new tuning method for a PID controller of a nonlinear system. The pro... more In this paper, we present a new tuning method for a PID controller of a nonlinear system. The proposed approach is an hybridization of the Artificial Bees Colony (ABC) and the Predator and prey (P\&P) behavior. The employed bees will explore new sources in the search space while running away from their predators. Simulations of the proposed algorithm are carried out over an inverted pendulum nonlinear system. Obtained performances are better then Genetic algorithm when compared in the same conditions.
International Journal of Intelligent Systems and Applications, 2014
the aim of this paper is to present a strategy describing a hybrid approach for the navigation of... more the aim of this paper is to present a strategy describing a hybrid approach for the navigation of a mobile robot in a partially known environment. The main idea is to combine between fuzzy logic approach suitable for the navigation in an unknown environment and spiking neural networks approach for solving the problem of navigation in a known environment. In the literature, many approaches exist for the navigation purpose, for solving separately the problem in both situations. Our idea is based on the fact that we consider a mixed environment, and try to exploit the known environment parts for improving the path and time of navigation between the starting point and the target. The Simulation results, which are shown on two simulated scenarios, indicate that the hybridization improves the performance of robot navigation with regard to path length and the time of navigation.
3rd International Conference on Systems and Control, 2013
In this paper, we present a new tuning method for a PID controller of a nonlinear system. The pro... more In this paper, we present a new tuning method for a PID controller of a nonlinear system. The proposed approach is an hybridization of the Artificial Bees Colony (ABC) and the Predator and prey (P\&P) behavior. The employed bees will explore new sources in the search space while running away from their predators. Simulations of the proposed algorithm are carried out over an inverted pendulum nonlinear system. Obtained performances are better then Genetic algorithm when compared in the same conditions.
International Journal of Intelligent Systems and Applications, Oct 8, 2014
In this paper an enhanced approach based on a modified biogeography optimization with predator an... more In this paper an enhanced approach based on a modified biogeography optimization with predator and prey behavior (PMBBO) is presented. The approach uses several predators with new proposed prey's movement formula. The potential of using a modified predator and prey model is to increase the diversification along the optimization process so to avoid local optima and reach the optimal solution quickly. The proposed approach is used in tuning the gains of PID controller for nonlinear systems (Mass spring damper and an inverted pendulum) and has given remarkable results when compared to genetic algorithm and classical BBO.
International Journal of Intelligent Systems and Applications, Aug 8, 2014
In this paper, we present a combination of sequential trained radial basis function networks and ... more In this paper, we present a combination of sequential trained radial basis function networks and fuzzy techniques to enhance the variable structure controllers dedicated to robotics systems. In this aim, four RBFs networks were used to estimate the model based part parameters (Inertia, Centrifugal and Coriolis, Gravity and Friction matrices) of a variable structure controller so to respond to model variation and disturbances, a sequential online training algorithm based on Growing-Pruning "GAP" strategy and Kalman filter was implemented. To eliminate the chattering effect, the corrective control of the VS control was computed by a fuzzy controller. Simulations are carried out to control three degrees of freedom SCARA robot manipulator where the obtained results show good disturbance rejection and chattering elimination.
This paper deals with the application of a variable structure observer developed for a class of n... more This paper deals with the application of a variable structure observer developed for a class of nonlinear systems to solve the trajectory tracking problem for rigid robot manipulators. The analyzed approach to observer design proposes a simple design methodology for systems having completely observable linear parts and bounded nonlinearities and/or uncertainties. This observer is basically the conventional Luenberger observer with an additional switching term that is used to guarantee robustness against modeling errors and system uncertainties. To solve the tracking problem, we use a control law developed for robot manipulators in the full information case. The closed loop system is shown to be globally asymptotically stable based on Lyapunov arguments. Simulation results on a 3-DOF robot manipulator show the asymptotic convergence of the vectors of observation and tracking errors.
Technological Advances in microelectronic and telecommunication fields enable the existence of ti... more Technological Advances in microelectronic and telecommunication fields enable the existence of tiny computing units, very small and more efficient. In the context of these new technologies, Wireless Sensor Networks (WSN) have emerged. The main research objective in WSN domain is the development of algorithms and protocols ensuring minimal energy consumption. Most proposed solutions are based on one-layer stack model approach. Recently, other works tend to exploit together many layers in order to optimize energy consumption. In this paper, we propose a Cross-Layer Medium Access Control (CL-MAC) protocol using two adjacent layers (MAC and Network) to economize energy for WSN. The basic idea behind our protocol is to wake-up only nodes belonging to a routing path from the source to the base station (Sink) by exploiting routing information while other nodes leave maintained as long time as possible in a sleep mode. The protocol is modeled using a time Petri net and validated by TiNA tool. The simulation results demonstrate the effectiveness of our proposal in terms of energy consumption and latency.
The present paper is dedicated to the presentation and implementation of an optimized technique a... more The present paper is dedicated to the presentation and implementation of an optimized technique allowing an on-line estimation of a robot manipulator parameters to use them in a computed torque control. Indeed the proposed control law needs the exact robot model to give good performances. The complexity of the robot manipulator and its strong non-linearity makes it hard to know its parameters. Therefore, we propose in this paper to use neuro-fuzzy networks Sequential Adaptive Fuzzy Inference System (SAFIS) to estimate the parameters of the controlled robot manipulator.
2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), 2012
The aim of this work is the combination of radial basis function networks (RBF) and fuzzy techniq... more The aim of this work is the combination of radial basis function networks (RBF) and fuzzy techniques to enhance the sliding mode controllers. In fact, three RBFs networks were used to estimate the model parameters and to respond to model variation and disturbances, a sequential training algorithm based on Kalman filter was implemented, and to eliminate the chattering effect, a fuzzy controller was designed. The hybrid sliding mode controller had shown a strong ability to get over noise and uncertainties. The former controller was used to control a two degree of freedom robot manipulator.
2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), 2012
Abstract: A sliding mode control has been a great interest in the control engineering community, ... more Abstract: A sliding mode control has been a great interest in the control engineering community, with many applications particularly in the robot manipulators control. This paper presents investigations into the development of Sliding Mode control approach based ...
International Journal of Intelligent Systems and Applications, 2014
In this paper, we present a combination of sequential trained radial basis function networks and ... more In this paper, we present a combination of sequential trained radial basis function networks and fuzzy techniques to enhance the variable structure controllers dedicated to robotics systems. In this aim, four RBFs networks were used to estimate the model based part parameters (Inertia, Centrifugal and Coriolis, Gravity and Friction matrices) of a variable structure controller so to respond to model variation and disturbances, a sequential online training algorithm based on Growing-Pruning "GAP" strategy and Kalman filter was implemented. To eliminate the chattering effect, the corrective control of the VS control was computed by a fuzzy controller. Simulations are carried out to control three degrees of freedom SCARA robot manipulator where the obtained results show good disturbance rejection and chattering elimination.
2013 IEEE International Conference on Industrial Technology (ICIT), 2013
ABSTRACT In this paper, we try to present a sliding mode with fuzzy-neural network controller for... more ABSTRACT In this paper, we try to present a sliding mode with fuzzy-neural network controller for nonlinear systems. It is a special nonlinear control method (SMC) which has quick response, insensitive to parameters variation and disturbance. Online identification for plants is not needed, it's very suitable for nonlinear system control, but in reality using the chattering reduction and elimination are key problem in SMC. By using a function-augmented sliding hyper plane, it is guaranteed that the output tracking error converges to zero in finite time which can be set arbitrarily. The fuzzy-neural network mainly Self Tuning Fuzzy Inference System (STFIS) is used to approximate the unknown system functions and switch item. Finally, the sliding-mode with fuzzy-neural network control is used to control single inverted pendulum and confirms the validity of the proposals. Results of simulations containing tests of robustness are presented and realized in MATLAB environment.
2012 IEEE International Symposium on Industrial Electronics, 2012
A robust control approach denoted sliding control of MIMO nonlinear system based on the output fe... more A robust control approach denoted sliding control of MIMO nonlinear system based on the output feedback linearization is developed to attenuate the parametric uncertainties. The scheme is dedicated to model of unmanned aerial vehicles (the quadrotor UAV). We assume that the model of the plant is not precise, due to nondeterministic knowledge of inertias parameters. Tracking control is used to stabilize the equilibrium of the system, while all the state supposed to be measurable. The analysis is based on tracking errors during transients and at the steady state, on performance, stability and robustness with respect to plant uncertainties. Simulation results are carried out.
2012 IEEE International Conference on Complex Systems (ICCS), 2012
This paper is dedicated to present the newly developed evolutionary algorithm: Biogeography based... more This paper is dedicated to present the newly developed evolutionary algorithm: Biogeography based optimization (BBO). It is based on the migration of information between habitats like in Biogeography. The BBO is then used to tune a PID controller of nonlinear systems where the parameters are optimized. Simulations of the proposed algorithm are carried out over an inverted pendulum and second on mass-spring damper system. Performances of the BBO are compared to those of genetic algorithm in PID tuning problem and the BBO gives acceptable results even best then GA.
3rd International Conference on Systems and Control, 2013
In this paper, we present a new tuning method for a PID controller of a nonlinear system. The pro... more In this paper, we present a new tuning method for a PID controller of a nonlinear system. The proposed approach is an hybridization of the Artificial Bees Colony (ABC) and the Predator and prey (P\&P) behavior. The employed bees will explore new sources in the search space while running away from their predators. Simulations of the proposed algorithm are carried out over an inverted pendulum nonlinear system. Obtained performances are better then Genetic algorithm when compared in the same conditions.
International Journal of Intelligent Systems and Applications, 2014
the aim of this paper is to present a strategy describing a hybrid approach for the navigation of... more the aim of this paper is to present a strategy describing a hybrid approach for the navigation of a mobile robot in a partially known environment. The main idea is to combine between fuzzy logic approach suitable for the navigation in an unknown environment and spiking neural networks approach for solving the problem of navigation in a known environment. In the literature, many approaches exist for the navigation purpose, for solving separately the problem in both situations. Our idea is based on the fact that we consider a mixed environment, and try to exploit the known environment parts for improving the path and time of navigation between the starting point and the target. The Simulation results, which are shown on two simulated scenarios, indicate that the hybridization improves the performance of robot navigation with regard to path length and the time of navigation.
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Papers by Mohamed Khelfi