Model-Free Predictive Sliding Mode Control for PMSM Drives Using Ultra-Local Method

Since some physical parameters of the motor are time-varying, the realized control performances are inevitably affected by the parameter mismatches in the sliding mode control (SM C). To fully eliminate the influences caused by the parameter mismatches and enhance the robustness of the conventional SMC, an ultra-local-based model-free predictive SMC is proposed in this paper, and used as the current controller in the permanent magnet synchronous motor (PMSM) driving system. A priori model is replaced by the ultra-local, in which physical parameters of the plant are not required anymore. The unknown terms of the plant are summarized as a single variable and online estimated by an extended state observer (ESO) to maintain a well model accuracy. The effectiveness and correctness are demonstrated by the simulation and experimental results, as well as the advantage of current quality and speed integral of time and absolute error (ITAE) with suitable robustness.     «

Since some physical parameters of the motor are time-varying, the realized control performances are inevitably affected by the parameter mismatches in the sliding mode control (SM C). To fully eliminate the influences caused by the parameter mismatches and enhance the robustness of the conventional SMC, an ultra-local-based model-free predictive SMC is proposed in this paper, and used as the current controller in the permanent magnet synchronous motor (PMSM) driving system. A priori model is rep...     »