Dynamic Cost Function Design of Finite-Control-Set Model Predictive Current Control for PMSM Drives

One of the clear advantages of finite-control-set model predictive control (FCS-MPC) is that several control targets and constraints can be contained in a cost function. However, the traditional fixed weighting factors cannot make each term in cost function fully express their performance, especially during a dynamic process. This paper proposes an FCS-MPC with a dynamic cost function based on fuzzy rules. The speed error and its change are used for tuning weighting factors adaptively by fuzzy method. The membership functions and fuzzy decision rules are built. The proposed method can improve the dynamic response, and the switching frequency is optimized at the same time. The performance is demonstrated in both simulation and experiment.

I. Introduction

Permanent Magnet Synchronous Motor (PMSM) is extensively adopted in industrial applications [1] [2]. It expresses significant advantages such as high efficiency and high power density [3]. Various methods have been proposed to achieve high performance control of PMSM drives and predictive control becomes attractive for high dynamic performance with the rapid development of computer teclnology [4].