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The advanced control method for solar-powered water pumping systems presented in this paper is based on a photovoltaic (PV) array that is interfaced with a high-gain boost converter (HGBC). A hybrid maximum power point tracking (MPPT) algorithm that combines particle swarm optimization (PSO) and artificial neural networks (ANN) is used to optimize energy extraction under changing irradiance. A sliding mode observer (SMO) with artificial intelligence is used to estimate rotor speed, increasing its robustness against noise and nonlinearities. Sufficient voltage levels are guaranteed for steady motor operation by the HGBC. Simulation results show reliable performance during irradiance fluctuations, accurate speed control with estimation errors below 2 %, and a smooth system startup. These results demonstrate the system's suitability for reliable and effective operation in stand-alone PV-driven water pumping applications.
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DOI: 10.1109/iccsc66714.2025.11135358
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