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An Integrated Observer Framework Based Mechanical Parameters Identification for Adaptive Control of Permanent Magnet Synchronous Motor

Liao Zhong, Zhaohua Liu, Lei Chen, Mingyang Lyu, Zhengheng Wang, Dian Wang, Faming Wu, Hua‐Liang Wei

2022Complex System Modeling and Simulation11 citationsDOIOpen Access PDF

Abstract

An integrated observer framework based mechanical parameters identification approach for adaptive control of permanent magnet synchronous motors is proposed in this paper. Firstly, an integrated observer framework is established for mechanical parameters' estimation, which consists of an extended sliding mode observer (ESMO) and a Luenberger observer. Aiming at minimizing the influence of parameters coupling, the viscous friction and the moment of inertia are obtained by ESMO and the load torque is identified by Luenberger observer separately. After obtaining estimates of the mechanical parameters, the optimal proportional integral (PI) parameters of the speed-loop are determined according to third-order best design method. As a result, the controller can adjust the PI parameters in real time according to the parameter changes to realize the adaptive control of the system. Meanwhile, the disturbance is compensated according to the estimates. Finally, the experiments were carried out on simulation platform, and the experimental results validated the reliability of parameter identification and the efficiency of the adaptive control strategy presented in this paper.

Topics & Concepts

Control theory (sociology)Observer (physics)InertiaTorqueState observerMechanical systemMagnetControl engineeringComputer scienceAdaptive controlEngineeringControl (management)PhysicsMechanical engineeringNonlinear systemClassical mechanicsQuantum mechanicsArtificial intelligenceThermodynamicsSensorless Control of Electric MotorsIterative Learning Control SystemsElectric Motor Design and Analysis