Passivity-Based Parameter Estimation and Position Control of Induction Motors via Composite Adaptation

Abstract

This paper proposes the parameters estimation and position control of an induction motor drive by using the composite adaptation scheme. First, in the rotor reference frame, the input-output linearization theory was employed to decouple the mechanical rotor position and the rotor flux amplitude at the transient state. An open-loop current model rotor flux observer was utilized for estimating the flux, and then the adaptive laws for estimating the rotor resistance, moment of inertia, viscous friction coefficient, and load torque. The passive properties of the flux observer, rotor resistance estimator, and composite adaptive position controller were analyzed based on the passivity theorem. According to the properties, the overall position control system was proved to be globally stable without using Lyapunov-type arguments. Experimental results are finally provided to show that the proposed method is robust to variations of the motor mechanical parameters, rotor resistance, and load torque disturbances. Moreover, good position tracking response and characteristics on parameter estimation can be achieved.