PROJECT TITLE :

Maximum Power Point Tracking Control of Photovoltaic Systems: A Polynomial Fuzzy Model-Based Approach - 2017

ABSTRACT:

This paper introduces a polynomial fuzzy model (PFM)-primarily based maximum power purpose tracking (MPPT) management approach to increase the performance and potency of the solar photovoltaic (PV) electricity generation. The proposed methodology depends on a polynomial fuzzy modeling, a polynomial parallel distributed compensation, and a add-of-squares (SOS) decomposition. The proposed methodology may be a generalization of the standard Takagi-Sugeno fuzzy models and linear matrix inequality, that showed its effectiveness in decreasing the tracking time and increasing the efficiency of the PV systems. In this paper, an instantaneous most power (DMP)-based mostly control structure is taken into account for MPPT. Using the PFM representation, the DMP-primarily based management structure is formulated in terms of SOS conditions. Unlike the traditional approaches, the proposed approach will not need exploring the maximum power operational point. Finally, the in depth studies and hardware-in-the-loop simulations are presented to point out the effectiveness of the proposed methodology.


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