Stable Simultaneous Inertia and Disturbance Torque Identification for SPMSM Drive Systems Subject to Mismatched Rotor Flux Linkage
Chengbo Yang, Bao Song, Yuanlong Xie, Shaowu Lu, Xiaoqi Tang
Abstract
In surface-mounted permanent magnet synchronous motor (SPMSM) drives, the distinguished orthogonal-principle-based method is presently popular for handling simultaneous inertia and disturbance torque estimation due to its simplicity and ease of implementation. Nevertheless, it is facing challenges posed by the rotor flux-linkage mismatch, zero-derivative constraint, and operating-condition limitation. To cope with these issues, this article presents an alternative scheme, which explores a stable simultaneous inertia and disturbance torque estimation with the real-time flux-linkage correction. First, an Adaline-based estimator is developed to acquire the disturbance torque. With an input-adaptive learning rate designed by the Lyapunov theory, this estimator can prevent potential convergence failure. Then, an extended sliding-mode observer for inertia estimation is proposed regarding the inertia as a new system state. By using the identified disturbance torque to devise an adaptive feedback gain, this observer guarantees the asymptotic error convergence. Finally, to counteract the flux-linkage mismatch, a flux-linkage observer with a time-varying learning rate is constructed utilizing the Adaline technique. Moreover, it attains robust convergence and only has one to-be-adjusted parameter. The effectiveness of our scheme is validated by abundant simulations and real-time experiments.