Optimized TSMC Control Based MPPT for PV System under Variable Atmospheric Conditions Using PSO Algorithm

In the present paper, we report a robust and efficient terminal sliding mode controller based particle swarm optimization (PSO-TSMC) for maximum power point tracking (MPPT) of photovoltaic (PV) system under variable atmospheric conditions. The PSO-TSMC controller combines the features of both terminal sliding mode control (TSMC) and particle swarm optimization (PSO) method. The proposed approach is designed based TSMC controller as robust nonlinear controller in order to make the PV system performs at the desired reference maximum power voltage (MPV) despite the atmospheric conditions variation, by regulating the control duty cycle. Moreover, the proposed approach applied TSMC controller with their optimal parameter by using PSO method. Furthermore, a comparative study, including the proposed PSO-TSMC controller, the standard TSMC and the conventional sliding mode control (SMC), is investigated under variable atmospheric conditions. Hence, simulation results reveal that the proposed approach assures more robustness against atmospheric conditions variation with best tracking performance and fast tracking response convergence in finite time compared to the other controllers (i.e. TSMC and SMC). (C) 2020 The Authors. Published by Elsevier B.V.