Deadbeat Predictive Current Control of High-Speed PMSM with TLS Based Multiparameter Online Identification

With the rated speed of Permanent magnet synchronous motor (PMSM) increases, the d-q-axis cross-coupling problem becomes more and more serious, which degrades the transient response and steady accuracy of current loop. Besides, the perturbation of PMSM electrical parameters also affects the model-based current controller performance. Therefore, an improved deadbeat predictive current control (DPCC) combined with a novel multiparameter online identification is proposed in this paper. First of all, the DPCC considering the cross-coupling is developed to improve the performance of current loop during high-speed range. The influence of DPCC and rotor position identification errors are also analyzed due to the mismatch of electrical parameters. After that, a total least squares (TLS) based online method is designed to identify phase inductance, resistance and rotor permanent magnet flux linkage. To solve the TLS problem in embedded control systems with limited resources, a novel iterative algorithm based on the excitatory and inhibitory learning (EXIN) method is developed. Besides, a multicycle step-by-step identification approach is also designed to solve the rank deficiency problem. Finally, the experimental platform is built based on a high-speed PMSM with a 60000 r/min rated speed. The experimental results verify the feasibility and effectiveness of the proposed method.