Robust fuzzy control of PV systems with parametric uncertainties

This presentation describes a new robust nonlinear fuzzy control (RNFC) problem for uncertain nonlinear systems and also presents a Takagi-Sugeno (TS) fuzzy model-based maximum power control approach. First, a maximum-power-voltage-based control scheme and direct maximum power control scheme are introduced for maximum power point tracking (MPPT). Furthermore, the MPPT's robustness to cope with varying atmosphere and system uncertainties is also discussed. Second, a nonlinear system with parametric uncertainties is represented by the TS fuzzy model. Next, in order to reduce the number of measured signals, a TS fuzzy observer is established for state feedback. Then the concept of parallel design compensation (PDC) is employed to design an RNFC from the TS fuzzy models. The sufficient conditions are formulated in the format of linear matrix inequalities (LMIs) to obtain the observer and controller gains. The effectiveness of the proposed controller design methodology is finally demonstrated through a photovoltaic (PV) panel array to maximize the PV power.