Robust fuzzy controller for photovoltaic maximum power point tracking

In this paper, the stability and robustness analyses of uncertain multivariable nonlinear control systems based on fuzzy logic approaches are presented. A system that comprises a Takagi-Sugeno (TS) fuzzy plant model and a fuzzy controller connected in closed-loop is first considered and second establishing fuzzy state observers. The TS fuzzy plant model represents an uncertain multivariable nonlinear system as a weighted sum of a number of sub-systems. Similarly, the fuzzy controller is a weighted sum of a number of sub-controllers. The concept of Parallel Design Compensation (PDC) is employed to design Grid-Point Fuzzy Controller (GPFC) from the TS fuzzy models. The sufficient conditions are formulated in the format of Linear Matrix Inequalities (LMIs). The effectiveness of the proposed controller design methodology is finally demonstrated through a photovoltaic panel array to maximize the PV power. In detail, we consider a dc/dc buck converter to regulate the output power of the photovoltaic panel array. Therefore, the proposed method provides an easier implementation form under strict stability analysis. Finally, the control performance is shown from the numerical simulation results.