Multi‐rate real‐time model‐based parameter estimation and state identification for induction motors

This study presents multi‐rate parameter and state estimation methods for the induction motor. Based on multi‐rate control theory and the extended Kalman filter (EKF) theory, a multi‐rate EKF algorithm including input and output algorithms is proposed for load torque estimation in the induction motor. The methods are implemented in real‐time on PC‐cluster node which acts as the controller for an induction motor experimental set‐up. Rotor time constant is a sensitive variable in indirect field‐oriented control method. A multi‐rate model reference adaptive system (MRAS) is proposed to estimate the rotor time constant in order to guarantee the high‐performance control of induction motor. Experimental result verified the effectiveness of the algorithms. Simulations compare the multi‐rate EKF algorithm with the traditional single‐rate EKF algorithm performance to show improved performance of load torque estimator. The comparison between the traditional MRAS and the multi‐rate MRAS shows the superiority of the proposed method, with a satisfactory accuracy.