Sinda Aloui

Improved fuzzy sliding mode control for a class of MIMO nonlinear uncertain and perturbed systems

In this paper, a stable adaptive fuzzy sliding mode based tracking control is developed for a class of nonlinear MIMO systems that are represented by input output models involving system uncertainties and external disturbances. The main contribution of the proposed method is that the structure of the controller system is partially unknown and does not require the bounds of uncertainties and disturbance to be known. First, a fuzzy logic system is designed to estimate the unknown function. Secondly, in order to eliminate the chattering phenomenon brought by the conventional variable structure control, the signum function is replaced by an adaptive Proportional Derivative (PD) term in the proposed approach. All parameter adaptive laws and robustifying control terms are derived based on Lyapunov stability analysis, so that convergence to zero of tracking errors and boudedness of all signals in the closed-loop system can be guaranteed. Finally, a mass-spring-damper system is simulated to demonstrate the validity and the effectiveness of the proposed controller.

Robust Adaptive Fuzzy Sliding Mode Control Design for a class of MIMO underactuated system

Abstract In this paper, a robust adaptive fuzzy controller which combines the sliding mode control with an adaptive Proportional Integral (PI) term is developed for a class of nonlinear Multi Inputs Multi Outputs (MIMO) underactuated systems with unknown parameters and in presence of external disturbances. The main contribution of the proposed method is that underactuated systems can be controlled in their original non square form. The problem of matrix singularity for this class of systems is solved by using the property of the regularized inverse and by introducing a compensator term in the proposed control law. The free parameters of the adaptive fuzzy controller are tuned on-line based on the Lyapunov approach. The overall adaptive fuzzy scheme guarantees the boundedness of all the closed-loop signals as well as the tracking errors. The validity of the proposed approach is shown by computer simulations.

Improved observer-based adaptive fuzzy tracking control for MIMO nonlinear systems

In this paper, a stable observer-based adaptive fuzzy controller which combines a sliding mode and an adaptive Proportional Integral (PI) controllers is developed for a class of nonlinear Multiple Input Multiple Output (MIMO) systems with unknown parameters and in presence of external disturbances. The free parameters of the adaptive fuzzy controller are tuned on-line based on the Lyapunov approach. The overall adaptive fuzzy scheme guarantees the uniform ultimate boundedness of all the closed-loop signals as well as the tracking errors. The validity of the proposed approach is shown by computer simulations of a two-link robotic manipulator.

Adaptive Fuzzy Sliding Mode Tracking Control of Uncertain Underactuated Nonlinear Systems

The trajectory tracking of underactuated nonlinear system with two degrees of freedom is tackled by an adaptive fuzzy hierarchical sliding mode controller. The proposed control law solves the problem of coupling using a hierarchical structure of the sliding surfaces and chattering by adopting different reaching laws. The unknown system functions are approximated by fuzzy logic systems and free parameters can be updated online by adaptive laws based on Lyapunov theory. Two comparative studies are made in this paper. The first comparison is between three different expressions of reaching laws to compare their abilities to reduce the chattering phenomenon. The second comparison is made between the proposed adaptive fuzzy hierarchical sliding mode controller and two other control laws which keep the coupling in the underactuated system. The tracking performances of each control law are evaluated. Simulation examples including different amplitudes of external disturbances are made.

Generalized fuzzy sliding mode control for MIMO nonlinear uncertain and perturbed systems

In this paper, a stable adaptive fuzzy sliding mode based tracking control is developed for a class of non-square nonlinear systems that are represented by input output models involving system uncertainties and external disturbances. The main contribution of the proposed method is that non-square systems are be controlled in their original non-square form instead of squaring them by adding or eliminating variables. First, a fuzzy logic system is designed to estimate the unknown function. Secondly, in order to eliminate the chattering phenomenon brought by the conventional variable structure control, the signum function is replaced by an adaptive Proportional Derivative (PD) term in the proposed approach. All parameter adaptive laws and robustifying control terms are derived based on Lyapunov stability analysis, so that the convergence to zero of tracking errors and the boudedness of all signals in the closed-loop system can be guaranteed. The efficiency of the proposed approach is shown by computer simulations.

Fuzzy Sliding Mode Control for Turbocharged Diesel Engine

In this work, Fuzzy Second Order and Adaptive Sliding Mode Control are developed for a Turbocharged Diesel Engine (TDE). In control design the TDE is represented by Multi-Output Multi-Input (MIMO) nonlinear model with partially unknown dynamics. To regulate the intake manifold pressure, the exhaust manifold pressure, the compressor flow and to estimate the unknown functions, a Sliding Mode Control (SMC) combined with Fuzzy Logic are firstly developed. Secondly to reduce the chattering phenomenon without deteriorating the tracking performance, two approaches are investigated. A special case of the Second Order Sliding Mode Controller (2-SMC): the super twisting sliding mode controller is developed. The results obtained using the Adaptive Sliding Mode Control (ASMC) are also presented to compare the performances of both methods. All parameter adaptive laws and robustifying control terms are derived based on Lyapunov stability analysis, so that convergence to zero of tracking errors and boudedness of all signals in the closed-loop system are guaranteed. Simulation results are given to show the efficiency of the proposed approaches.

Robust fuzzy tracking control for a class of perturbed non square nonlinear systems

A stable adaptive fuzzy control based tracking control is developed for a class of Multi Input Multi Output (MIMO) non square nonlinear systems with external disturbances using sliding mode algorithm. This control algorithm further justifies that non square systems can be controlled in their original non square form instead of squaring them by adding or eliminating variables. This method integrates adaptive fuzzy systems to approximate the unknown nonlinear functions. Then, in order to reduce the chattering phenomenon without deteriorating the tracking performances, the discontinuous term in the conventional sliding mode technique is replaced by an adaptive Proportional Integral (PI) term. All parameter adaptive laws are derived based on Lyapunov stability analysis. The overall adaptive fuzzy scheme guarantees the convergence to zero of tracking errors as well as the boundedness of all signals in the closed-loop system. The validity of the proposed approach is shown by computer simulations.

Robust tracking adaptive fuzzy control for a class of MIMO nonlinear systems

In this paper, the main results are focused on the design of a robust tracking controller for a class of nonlinear Multi Input Multi Output (MIMO) systems involving uncertainties and external disturbances. A hybrid adaptive robust tracking control scheme which is based upon a combination of sliding mode technique, Proportional Integral (PI) controller and fuzzy control design is developed. Based on the Lyapunov theorem, the proposed adaptive fuzzy control system can guarantee the global stability and the robustness of the whole closed-loop system and reduce the chattering problem without deteriorating the tracking performances. A simulation example is finally included to illustrate the tracking performances of the proposed approach.

Robust control approach for a diesel engine: AMESim validation

Advanced Modeling Environment for performing Simulations of engineering systems (AMESim) is a multi-domain software that allows interconnection between different type of physical systems. It also allows to reproduce their dynamic behaviors under various scenarios and to analyze their operation. In this paper, AMESim software is introduced in order to validate the developed control laws. In fact, an AFSMC approach is developed for a TDE. Adaptive PD term is integrated to eliminate the chattering phenomenon without deteriorating the tracking performances and fuzzy logic systems are introduced to approximate the unknown functions. Adaptive parameters are obtained basing on Lyapunov stability analysis to guarantee stability of closed loop system. Simulations are presented to illustrate the performance of the developed approach.