Abstract
This paper addresses the robust fuzzy scheduler controller (RFSC) for nonlinear systems which is robust enough to stabilize a nonlinear system with parametric uncertainties, wind disturbance, and give an acceptable closed-loop performance in the presence of state variables unavailable for measurements. The Takagi-Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the nonlinear system. The concept of parallel distributed compensation (PDC) is employed to design fuzzy control from the TS fuzzy models. Sufficient conditions are formulated in the format of linear matrix inequalities (LMIs). The proposed controller design methodology is finally demonstrated through the model of wind energy systems (WES) with a doubly-fed induction generator (DFIG) to illustrate the effectiveness of the proposed method. The proposed algorithm maximizes the produced power and is able to maintain a stable system during the parameter uncertainties.
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