Implementation an adaptive fuzzy NARX controller for MPPT PV supplied DC pump motor

This paper presents an application of a novel fuzzy NARX model for the identification of the optimal operating point of a PV supplied DC motor pumping system. A modified genetic algorithm (GA) is used to train the proposed fuzzy NARX-based controller for the identification of the maximum power point of the solar panel. The developed algorithm based on matching of the solar panel to the motor load through a buck-boost power converter so that the combined system can operate at the optimum point. The input parameters to the fuzzy NARX model are solar radiation and working temperature meanwhile the output parameter is the converter chopping ratio corresponding to the maximum power output of the solar panel or gross mechanical energy output (GME) of the combined PV system. The converter chopping ratios at different solar radiation and temperature are obtained from the adaptive fuzzy NARX-based controller. Simulation results proved the performance and efficiency of the proposed fuzzy MISO NARX controller.

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