AN ENHANCED MPPT BASED ON INTEGRAL SLIDING MODE CONTROL AND ARTIFICIAL NEURAL NETWORK FOR PV PUMPING SYSTEM - ELIDRISSI, RAFIKA (Indonesian Journal of Electrical Engineering and Computer Science, 2020)
This paper proposes a maximum power point tracking (MPPT) control method for a photovoltaic (PV) pumping system based on a nonlinear integral sliding mode approach. The system?s power circuit comprises of a solar panel, a boost-up converter and a DC motor feeds a water pump. Two loops are in the control system: the first, provides the reference voltage, that is given by intelligent method based on artificial neural network (ANN), according with the maximum power point (MPP), for the integral sliding mode controller in the second loop that regulates the PV array voltage in MPP. This is done through adjustment of the DC-DC boost converter duty ratio. The proposed approach is compared to the integral backstepping approach. Simulation results depict the proposed regulator effectiveness and robustness in relation to rapidly irradiance and temperature changes.