Encoderless current predictive control of synchronous reluctance motor by extended kalman filter based state estimation

Under the renunciation of sensor technology, encoderless control has been investigated for electrical drives, and consequently, the overall cost is reduced and system reliability is enhanced. In this paper, a robust method for encoderless current predictive control (CPC) for synchronous reluctance motor (SynRM) is presented and simulated. The presented CPC replaces the PI current controllers used in the conventional field-oriented control to approach where employes the discrete model of SynRM for predicting the upcoming values of the currents for all the possible switching vectors of the converters. An extended Kalman filter (EKF) is presented for encoderless control to estimate the position/speed of the rotor. Since the performance of the presented approach basically depends on the accuracy of the SynRM parameters, online parameter estimation is incorporated in the presented control strategy based on EKF. The unknown parameters (PI parameters and EKF covariance matrices) of the control method are tuned precisely using particle swarm optimization (PSO). The results reveal the robustness and reliability of the presented control approach.