[Objective]One-step and two-step model-free predictive current control (MFPCC) for permanent magnet synchronous motor (PMSM) system is established to address the strong parameter dependence issue in model predictive current control (MPCC).[Method]Based on the ultralocal model,one-step and two-step MFPCC for PMSM was implemented. The differential algebraic method was used to estimate uncertain parts of the first-order and second-order ultralocal models. The effect of the window sequence length of the ultralocal model on control performance was analyzed,along with the parameter robustness of the ultralocal model-based one-step and two-step MFPCC for PMSM with parameter variations. Real-time experiments were conducted to verify the results.[Results]Simulation and real-time experimental results showed that the window sequence length of the first-order ultralocal model significantly impacted the control performance. Increasing the window sequence length improved control performance until saturation. The window sequence length of the second-order ultralocal model had a smaller effect on control performance. The ultralocal model-based one-step and two-step MFPCC for PMSM showed strong parameter robustness with parameter variations. With the increase in window sequence length,the computational time for the ultralocal model increased slightly,but the overall real-time performance was minimally affected.[Conclusion]The ultralocal model-based one-step and two-step MFPCC for PMSM is feasible and demonstrates strong parameter robustness. The real-time performance of the ultralocal model-based one-step MFPCC is comparable to that of the conventional one-step MPCC. The ultralocal model-based two-step MFPCC exhibits slightly better real-time performance than the conventional two-step MPCC.
关键词
永磁同步电机/无模型预测电流控制/超局部模型/模型预测电流控制/鲁棒性/实时性
Key words
permanent magnet synchronous motor/model-free predictive current control/ultralocal model/model predictive current control/robustness/real-time performance
维普
万方数据