Maher Kharrat

T-S fuzzy maximum power point tracking control of photovoltaic conversion system

This paper propose a Takagi-Sugeno (T-S) fuzzy based reference model to deal with Maximum Power Point Tracking (MPPT) problem applied to a photovoltaic (PV) system. An MPP searching algorithm is used in the global MPPT structure to generate the optimal output boost voltage. It provides a good MPP tracking performance in the case of rapidly changing climatic conditions, and it reaches the maximum power point in less time with no oscillations in steady-state. The fuzzy controller is introduced in the global scheme in order to force the PV system to converge to the reference trajectory. the stability analysis and control design problems can be reduced to linear matrix inequality (LMI) problems. Simulation results are provided to illustrate the developed fuzzy controller in this paper.

Control Strategies for the Grid Side Converter in a Wind Generation System Based on a Fuzzy Approach

Abstract Two techniques for the control of a grid side converter in a wind energy conversion system. The system is composed of a fixed pitch angle wind turbine followed by a permanent magnet synchronous generator and power electronic converters AC-DC-AC. The main interest is in how to control the inverter in order to ensure the stability of the DC link voltage. Two control methods based on the fuzzy approach are applied and compared. First, a direct Mamdani fuzzy logic controller is presented. Then, a T-S fuzzy controller is elaborated based on a T-S fuzzy model. The Lyapunov theorem and H-infinity performance are exploited for stability analysis. Besides, the feedback controller gains are determined using linear matrix inequality tools. Simulation results are derived in order to prove the robustness of the proposed control algorithms and to compare their performances.

Comparison of adaptive input-output linearization & fuzzy sliding-mode control for induction motor

This paper presents a comparison between adaptive input-output linearization and adaptive fuzzy sliding mode control (FSMC) for induction motor. At first, we describe the adaptive linearization control method, which consists in the cancelling of the nonlinearities and decoupling between speed and flux of the system when Rr and TL are unknowns constants. The adaptive sliding mode control, which is insensitive to parameter variations and external disturbances. The substituting of discontinuous control by fuzzy system can be solution for the chattering problem and minimize the control effort.

Maximum power point tracking of a wind generation system based on T-S fuzzy model

The current paper is presenting a Takagi-Sugeno (T-S) fuzzy controller designed for a wind generation system in the objective of Maximum Power Point Tracking (MPPT). The considered Wind Energy Conversion System (WECS) is composed of a wind turbine and a Permanent Magnet Synchronous Generator (PMSG) associated to an AC-DC converter. First, the WECS fuzzy model is presented based on T-S approach. Next, the proposed controller is designed using Linear Matrix Inequalities (LMI) techniques and Lyapunov stability approach. Simulation results bring out the efficiency of the proposed scheme.

Backstepping and T.S fuzzy control for induction machine

In this paper, we present an application of a Takagi Sugeno (TS) Fuzzy logic backstepping control for enhancing performance of the machine drive. The equations states of induction machine are described in a d-q frame related to the rotating stator field. In the first step, the state feedback linearization technique is used for decoupling speed and flux controls. In the second step, we have been developed a control scheme basis of fuzzy backstepping. The simulation results in MATLAB environment show that the proposed scheme gives a satisfactory performance.