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.