基于MRAS的永磁同步电动机非线性参数辨识仿真研究与实现

Simulation Research and Implementation of Nonlinear Parameter Identification for PMSM based on MRAS

针对永磁同步电动机(Permanent Magnet Synchronous Motor,PMSM)在工业自动化系统控制过程中产生的参数畸变和漂移现象,导致PMSM的自身转速和电磁转矩无法有效保持稳定,本文提出一种基于模型参考自适应方法(Model Reference Adaptive System,MRAS)的非线性参数辨识算法模型。通过在线监测被控PMSM的主控参数来进行动态追踪和修正,强化被控PMSM自身转速和输出转矩的稳定性;最后通过PSIM仿真环境对新算法模型进行仿真验证。结果表明,本文提出的新型PMSM非线性数学模型能够与MRAS经典算法构成完整运行框架,进一步强化电机控制系统对PMSM被控参数的动态辨识和修正,削弱PMSM运行过程中的参数畸变和漂移现象,改善了PMSM在非线性参数工况下的运行稳定性,为未来搭建PMSM非线性闭环辨识控制系统实物平台提供理论支持。

In view of the parameter distortion and drift of permanent magnet synchronous motor(PMSM)in the control process of industrial automation system, resulting in the inability of PMSM to maintain its own speed and electromagnetic torque stable effectively, a nonlinear parameter identification algorithm model based on model reference adaptive system(MRAS)is proposed in this paper.Through on-line monitoring of the main control parameters of the controlled PMSM,dynamic tracking and correction are carried out to strengthen the stability of the speed and output torque of the controlled PMSM;Finally, the new algorithm model is simulated and verified by PSIM simulation environment.The results show that the new PMSM nonlinear mathematical model proposed in this paper can form a complete operation framework with the classical MRAS algorithm, further strengthen the dynamic identification and correction of PMSM control parameters by the motor control system, weaken the parameter distortion and drift phenomenon in the operation process of PMSM,improve the operation stability of PMSM under nonlinear parameter conditions, and provide theoretical support for building the physical platform of PMSM nonlinear closed-loop identification and control system in the future.