Moez Allouche

Fuzzy Tracking Control for Indirect Field-oriented Induction Machine Using Integral Action Performance

Abstract This paper deals with the synthesis of fuzzy controller applied to the induction motor with a guaranteed H∞ tracking performance. First, the Takagi-Sugeno fuzzy model is employed to approximate a nonlinear system in the synchronous d-q frame rotating with electromagnetic field-oriented. Next, a fuzzy observer-based fuzzy tracking controller is designed to stabilize the induction motor and guaranteed a minimum disturbance attenuation level for the closed-loop system. The rotor flux is unavailable for measurement and it is estimated by a fuzzy observer. An integral action is added to the new parallel distributed compensation fuzzy controller related to the tracking to avoid static errors. The gains of fuzzy control and fuzzy observer are obtained by solving a set of Linear Matrix Inequality. Finally, simulation result is given to demonstrate the controller’s effectiveness.

Robust Sensor Fault-Tolerant Control of Induction Motor Drive

This paper presents an active fuzzy fault-tolerant control (FTC) strategy for induction motor that ensures the performances of the field-oriented control (FOC). In the proposed approach, a robust controller is synthesized in order to compensate for both the resistance variation, the load torque disturbance, and the sensor fault. The physical model of induction motor is approximated by the Takagi–Sugeno (T–S) fuzzy technique in the synchronous d-q rotating frame. Fuzzy descriptor observer is introduced to estimate simultaneously the system state and the sensor faults. A robust feedback state tracking control is proposed to guarantee the control performances by minimizing the effect of the load torque and the uncertainties. The proposed controller is based on a T–S reference model in which a desired trajectory has been specified. The performances of the trajectory tracking are analyzed using the Lyapunov theory and the

Multiobjective maximum power tracking control of photovoltaic systems: T-S fuzzy model-based approach

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A Takagi-Sugeno fuzzy control of induction motor drive: experimental results

L2 optimization. Observer and controller gains are obtained by solving a set of LMIs constraint. To highlight the effectiveness of the proposed control simulation, results are introduced for a 1.5 KW induction motor.

Sensor fault tolerant control for induction motor

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.

Fuzzy sensor fault-tolerant control of an induction motor

This paper presents a multiobjective maximum power point tracking (MPPT) control for photovoltaic (PV) system to guarantee both

State Feedback Tracking Control for Indirect Field- oriented Induction Motor Using Fuzzy Approach

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