Moment of Inertia Identification based on Particle Swarm Optimization Model Reference Adaptive for Permanent Magnet Synchronous Motor

2018 International Conference on Advanced Technologies in Energy, Environmental and Electrical Engineering

能源学;生态环境科学;无线电电子学

Zhu, Mengmei^1 ; Zhou, Guangxu^1 ; Hou, Dongdong^1 ; Mu, Yongyun^1 ; Gao, Jia^1 ; Song, Ningran^1

Institute of Automation, Qilu University of Technology (Shandong Academy of Sciences), Shandong Provincial Key Laboratory of Automotive Electronics Technology, Ji'nan Shandong, China^1

关键词: Dynamic performance;    Fast convergence speed;    Model reference adaptive;    Optimization ability;    Particle swarm optimization algorithm;    Particle swarm optimization models;    Permanent Magnet Synchronous Motor;    Stability and convergence;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/223/1/012011/pdf
DOI  :  10.1088/1755-1315/223/1/012011

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

In order to improve the dynamic performance and robustness of permanent magnet synchronous motor (PMSM) servo system, the moment of inertia identification based on model reference adaptive algorithm is studied. According to the problem that the stability and convergence response speed of the model reference adaptive identification (MRAI) algorithm can not be combined at the same time, the particle swarm optimization (PSO) algorithm is used to optimize the model reference adaptive gain coefficient to realize the fast and stable identification of the moment of inertia. The simulation results showed that the method has strong optimization ability, fast convergence speed, small oscillation amplitude and good stability.