Adaptive Parameter Estimation and Position Control of Induction Motors Based on Passivity Theorem
This paper presents the passivity-based rotor resistance and mechanical paramters estimation, and the position control for induction motors. Firstly, the input-output linearization theory is employed to decouple the rotor flux amplitude and the rotor position at the transient state. An open-loop current model flux observer then estimates the rotor flux. Furthermore, we adopted the gradient algorithm to design adaptive laws to estimate the rotor resistance, moment of inertia, viscous coefficient, and load torque. The passive properties of the feedback connection of the rotor flux observer to the rotor resistance estimator, and the position controller are analyzed by the passivity theorem. According to the properties, the overall control system is proved to be globally stable without using Lyapunov-type arguments. Finally, experimental results are provided to show that the proposed method is robust to variations of the mechanical parameters and load torque disturbances. Moreover, good position tracking response and parameters estimating characteristic can be obtained.
Dongming Guo, Jun Wang, Zhenyuan Jia, Renke Kang, Hang Gao, and Xuyue Wang
J. Y. Chen and B. Y. Lee, "Adaptive Parameter Estimation and Position Control of Induction Motors Based on Passivity Theorem", Materials Science Forum, Vols. 626-627, pp. 489-494, 2009