Stability-guaranteed predictive sliding surface control of silicon carbide dual-output nine-switch inverter

In this study, a finite control set model predictive control strategy is proposed for a nine-switch converter system. The predictive control routine with discrete-solution space in energy transformation applications is widely used and offers a satisfactory closed-loop operation. However, the stability analysis of the predictive control method is a challenging task, and the practical stability approaches are applied to examine the closed-loop stability characteristics. Designing the guaranteed-stability predictive control is not an easy task since even the norm choice of the objective function may result in closed-loop instability. Regarding closed-loop stability, stability-guaranteed predictive sliding surface control approach is introduced in this study. The multi-objective cost function is reformulated in the proposed method as a sliding surface function usually used in sliding mode control methods. Thus, the best-suited control input that meets the sliding mode control stability criterion is picked. The proposed reformulation process enables the sliding surface function as an objective function, and the sliding surface function is gauged for each legitimate switching combination. The proposed control method is experimentally verified by using a 3.2 kW silicon carbide nine-switch inverter prototype. The experimental results prove that the proposed method guarantees closed-loop stability, and dual-AC load control is achieved.