Tuning of extended Kalman filter using grey wolf optimisation for speed control of permanent magnet synchronous motor drive

Abstract

This paper deals with tuning of extended Kalman filter (EKF) using grey wolf optimisation (GWO) for sensor less speed control of permanent magnet synchronous motor (PMSM) drive. A real-coded GWO is used to optimise the noise covariance matrices of EKF in an off-line manner. The optimised values of these matrices are injected into the filter, thereby ensuring filter stability and accuracy in the estimation of rotor speed, position and machine states. The estimated speed from EKF is fed back to the speed controller and controller gains Kp and Ki are again tuned using GWO algorithm. The state and measurement covariance matrices improve the convergence of estimation process and quality of the estimated states. The simulation results show the superior performance of the proposed method when compared to particle swarm optimisation (PSO) method.