Particle Swarm-Based Terminal Sliding Mode Control with Grey Predictor of a Single-Phase Inverter for Electric Vehicles

This paper proposes a particle swarm-based terminal sliding mode control with grey predictor, and then the proposed controller is applied for the single-phase inverter of the electric vehicle. The proposed controller has the advantages of terminal sliding mode control (TSMC), grey predictor (GP), and particle swarm optimization (PSO). The TSMC can force the system tracking error to converge to zero in finite time, but the chattering and steady-state errors still happen. The GP is thus employed to lessen the chattering or reduce the steady-state errors when system uncertainty bounds are overestimated or underestimated. Also, the control gains of the TSMC with GP can optimally be tuned by the use of the PSO for achieving more precise tracking. Experimental results on a single-phase inverter laboratory prototype controlled by a digital-based controller are given to conform that the proposed controller can lead to low total harmonic distortion (THD) and fast dynamic response under rectifier-type loading conditions and fast dynamic response under step change loading conditions.