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This paper deals with the synthesis of fuzzy controller applied to the induction motor with a guaranteed model reference tracking performance. First, the Takagi-Sugeno (T-S) fuzzy model is used to approximate the nonlinear system in the synchronous d-q frame rotating with field-oriented control strategy. Then, a fuzzy state feedback controller is designed to reduce the tracking error by minimizing the disturbance level. The proposed controller is based on a T-S reference model in which the desired trajectory has been specified. The inaccessible rotor flux is estimated by a T-S fuzzy observer. The developed approach for the controller design is based on the synthesis of an augmented fuzzy model which regroups the model of induction machine, fuzzy observer, and reference model. The gains of the observer and controller are obtained by solving a set of linear matrix inequalities (LMIs). Finally, simulation and experimental results are given to show the performance of the observer-based tracking controller.

This paper deals with the synthesis of a state feedback control law to reach some desired dynamic performances of an induction motor. The specification on the closed-loop poles is given in terms of clustering region such as the Ellipsoid Matrix Inequality εMI-region or the Extended Ellipsoid Matrix Inequality εεMI-region. The problem of robust matrix root-clustering analysis is studied. The considered matrix is complex and subject to parameter dependent norm-bounded uncertainties. The clustering regions are unions of convex and possibly disjoint and non-symmetric sub-regions of the complex plane. An aggregation technique approach is used to compute a static state feedback control law which performs a partial pole placement. The proposed clustering conditions are then formulated through an LMI approach. The simulation results provide a good compromise between dynamic performances and some robustness aspects of the controlled system.