Robust Predictive Current Control of PMLSM with Extended State Modeling Based Kalman Filter: For Time-Varying Disturbance Rejection

This paper proposed a robust deadbeat predictive current control (PCC) of the permanent magnet linear synchronous machine (PMLSM) with an extended state modeling (ESM) based Kalman filter (KF) for both the state and disturbance estimation. First, the disturbance dynamics of the PMLSM electrical subsystem is analyzed in detail and then the ESM is constructed as considering the disturbance as a higher order integrator motivated by the main idea of the extended state observer. Second, the KF for the current prediction with reduced noises and the disturbance estimation due to the parameter variation is designed combining with the ESM. Furtherly, the robust PCC is introduced with the ESM-based KF. Finally, the parameter tuning for the ESM-based KF is discussed with the discrete simulation and then the experimental results are given under the single current closed loop and the double cascade position-current loop with linear-varying parameter. Both the simulation and experimental results verify the effectiveness of the proposed scheme.