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Contribution to variable structure control based on the approach of fuzzy modeling of Ben-Ghalia for induction motor with Luenberger observer

Barazane L., Khwaldeh A., Krishan M. M., Sicard P.

Archives of Control Sciences

2008

Vol. 18, no. 4

453-476

Sliding mode and fuzzy logic control have been combined together in a variety of ways. In this paper, a novel direction to design fuzzy sliding controllers is proposed based on the approach of Ben-Ghalia et al. Which is able to provide a fuzzy set based on a decoupled and linear system obtained after the application of the feedback- linearization control to the model of an induction motor. On the other hand, a Luenberger observer is conceived in the present work to observe the rotor flux in the motor which is too important to permit the application of fuzzy modeling approach and ensure the optimal and required performances . Furthermore, another objective to use such an observer consists in stabilizing the system and rejecting the disturbances when the system is subjected to uncertainties. Furthermore, to overcome the problem of the chattering phenomenon generated by the application of conventional sliding mode control applied to the cascade structure of the motor, the approach of fuzzy sliding mode control based on the fuzzy modelling proposed by Ben-Ghalia is used. The robust fuzzy control design is made feasible without resorting to model simplification or imposing restrictive conditions on the system uncertainty. Finally, simulation results proves the capability of the proposed process to ensure a good performances and robustness which is the principal aim of this research

New approach to linguistic fuzzy modeling of induction motor fed by PWM voltage source inverter

Barazane L., Krishan M. M., Khwaldeh A., Sicard P.

Archives of Control Sciences

2007

Vol. 17, no. 2

209-235

In this paper, a new approach of linguistic fuzzy modeling proposed by Ben-Ghalia et al. is applied to induction motor. Thus, a classical model is first given together with the most used asynchronous motor control strategy, which is the pole assignment. After more, in order to minimize the dependence of the system to parameter variations and external perturbations, and reduce the number of variable states, a new model of the original system is proposed. This model is too simple and is suitable to cognitive approach such as fuzzy modeling. Then, fuzzy modeling of an uncertain system using the approach of Ben-Ghalia et al. to reduce the effects of imperfections of the classical modeling are introduced. In addition, their applications in the fuzzy sliding mode control of the asynchronous motor are presented. Finally, Simulation results reveal some very interesting features and show that the proposed fuzzy model has great potential for use as an alternative to the approximation of the conventional model of induction motor taking into account the effect of system model uncertainties and gives a good performances in sliding mode control.