Dynamic Performance Optimization of Deadbeat Predictive Current Control for PMSM by Gain Self-Tuning Technology

Abstract

In this article, a deadbeat predictive current control (DPCC) method based on gain factor self-tuning technology is proposed, which can effectively improve the dynamic response performance and robustness of the control system. Since the performance of DPCC is highly dependent on parameter accuracy, this article establishes a closed-loop transfer function model of the DPCC method and analyzes in detail the impact of parameter mismatch on the current dynamic response performance. Then, the current error caused by parameter mismatch is suppressed by designing the gain factor, on this basis, a parameter self-tuning algorithm based on gradient descent optimization method is constructed. Compared with traditional parameter identification algorithms, the proposed method has the advantages of strong versatility and greatly reduces computational burden. Finally, the accuracy of the tuning results of the proposed method is proved by experimental results, which effectively suppresses the influence of parameter mismatch and improves the current response performance.