Optimized sliding surface predictive control of a voltage source inverter with improved steady-state performance

Abstract

In this paper, an optimized sliding surface predictive control of a three-phase voltage source inverter is introduced. In power electronics, the model predictive control method (MPC) is broadly used and applied to a wide range of energy conversion systems. However, analyzing the stability of the MPC is not a straightforward task, and Lyapunov-based approaches are used to examine the stability characteristics in most cases. MPC is a nonlinear control technique, and the traditional frequency -domain stability tools cannot be used to examine the closed-loop stability. Therefore, a poor design of the MPC without considering the stability may worsen the system performance. Even the norm choice of the objective function leads to closed-loop instability, for example, t1 norm is not a sufficient choice to guarantee the global asymptotical stability. Even though t1 norm offers a low computational burden during the online optimization process, the system may suffer from closed-loop instability. For all these reasons, a stability-guaranteed objective function design procedure is proposed in this paper. The proposed objective function selection process is based on the sliding-mode control theory. The objective function is reformulated as a sliding surface function, and the switching combination that satisfies the sliding mode control stability criteria is selected as an optimum input. The mathematical concepts are experimentally validated, and the results demonstrate the potency of the proposed strategy. (c) 2021 Published by Elsevier Ltd on behalf of ISA.