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This paper presents a unified T-S fuzzy model-based maximum power control approach to enhance the efficiency and robustness of the solar photovoltaic (PV) power generation. First, the maximum-power-voltage-based control scheme and direct maximum power control scheme are introduced for the maximum power point tracking (MPPT). By using T-S fuzzy model representation, the two MPPT control schemes are formulated to an output tracking control problem in a unified form. Then, the T-S fuzzy observer and controller are developed to achieve asymptotic MPPT for uncertain PV power systems, where the controller and observer gains are able to be separately solved from novel linear matrix inequality formulation. Furthermore, the MPPT robustness is also discussed in the presence of rapidly changing atmosphere and external disturbances. Different from the traditional MPPT approaches, the proposed T-S fuzzy controller does not require searching the maximum power operational point and using coordinate transformation. All the buck, boost, or buck-boost converters can be used to achieve MPPT in the same control method. Finally, the satisfactory performance is shown from the simulation and experimental results.Index Terms-Maximum power point tracking (MPPT), PV system, T-S fuzzy model, uncertainty.

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This paper presents a maximum power point track ing (MPPT) control method for high efficient direct methanol fuel cell (DMFC) generation systems via T-S fuzzy model. In detail, we consider a DC/DC boost converter and incremental resistance method to regulate the output power of the DMFC to increase the output power under various conditions. First, the nonlinear boost converter system is represented by the T-S fuzzy model based control. Then, a fuzzy MPPT controller is proposed to achieve the MPPT control, in which the controller gains are obtained by solving linear matrix inequalities (LMIs). Finally, the satisfactory performance is shown from the simulations even under varying fuel cell conditions.