A New Load Adaptive Identification Method Based on an Improved Sliding Mode Observer for PMSM Position Servo System

被引:39
|
作者
Lu, Wenqi [1 ]
Tang, Bo [1 ]
Ji, Kehui [1 ]
Lu, Kaiyuan [2 ]
Wang, Dong [2 ]
Yu, Zhijun [3 ]
机构
[1] Zhejiang Sci Tech Univ, Fac Mech Engn & Automat, Hangzhou 310018, Peoples R China
[2] Aalborg Univ, Dept Energy Technol, DK-9220 Aalborg, Denmark
[3] Jiangsu Yuandong Elect Mfg Co Ltd, Taizhou 225500, Peoples R China
关键词
Torque; Observers; Servomotors; Mathematical model; Switches; Cutoff frequency; Low pass filters; Adaptive identification; high-precision positioning; improved sliding mode observer (SMO); position servo system;
D O I
10.1109/TPEL.2020.3016713
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The effective identification of the load torque is one of the key methods to improve the positioning accuracy of the position servo system, and the sliding mode observer (SMO) is a common identification method in the speed control system because of its advantages of insensitive parameters and easy physical realisation. However, the existing SMO cannot achieve high precision and high response identification of load torque in the full speed range when the motor is running at variable-speed or variable-load, which limits its application in the position servo system. Based on the analysis of the stability and the adaptive law of feedback gain coefficient, an improved SMO for adaptive identification based on adaptive control and improvement of cut-off frequency is proposed. To verify the proposed method, the dedicated simulation model and test platform are built. The results show that the proposed observer can realize the adaptive identification of the load torque under the condition of variable-speed or variable-load, and the estimation accuracy is high. The position servo system designed by the proposed observer can improve the response against load change, which is an effective method for high-precision positioning control of the position servo system with a variable-speed or variable-load.
引用
收藏
页码:3211 / 3223
页数:13
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