Abstract
This paper presents a multiobjective maximum power point tracking (MPPT) control for photovoltaic (PV) system to guarantee both \(H_{2}\) optimal control and \(H_{\infty }\) model reference tracking performance simultaneously. First, the Takagi and Sugeno (T–S) fuzzy model is employed to describe the dynamic behavior of DC–DC boost converter. Then, based on this exact T–S fuzzy representation, multiobjective \(H_{2}/H_{\infty }\) MPPT controller is designed to minimize concurrently the \(H_{2}\) tracking error and \(H_{\infty }\) disturbance attenuation level for the PV system. A specified T–S reference model is constructed to provide the desired trajectory which must be tracked. An MPP searching algorithm is also added in the global MPPT structure to generate the optimal PV current which is considered as input control for the T–S reference model. Finally, simulation results are given to illustrate the optimal tracking performance of the proposed fuzzy controller even when rapidly changing climatic conditions.
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Allouche, M., Dahech, K. & Chaabane, M. Multiobjective maximum power tracking control of photovoltaic systems: T-S fuzzy model-based approach. Soft Comput 22, 2121–2132 (2018). https://doi.org/10.1007/s00500-017-2691-7
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DOI: https://doi.org/10.1007/s00500-017-2691-7