Design of the Self-Adaptive Sliding Mode Position Controller based on Genetic Algorithm Optimization for the Servo Motor Drive System

被引：0

作者：

Jiao, Leiming ^{[1
]}

Luo, Yanhong ^{[1
]}

Zhang, Pengqiao ^{[2
]}

Li, Linlin ^{[3
]}

Zheng, Xiangtian ^{[4
]}

Qi, Ge ^{[1
]}

Jia, Hong ^{[5
]}

Liu, Hengyu ^{[1
]}

机构：

[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang, Liaoning, Peoples R China

[2] State Grid Liaoning Elect Power Co Ltd, Yingkou Power Supply Co, Yingkou, Peoples R China

[3] Qianhai Shenzhen FellowPlus Internet Financial Se, Beijing, Peoples R China

[4] Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R China

[5] State Grid Chaoyang Elect Power Supply Co, Chaoyang, Liaoning, Peoples R China

来源：

2017 IEEE 3RD INFORMATION TECHNOLOGY AND MECHATRONICS ENGINEERING CONFERENCE (ITOEC) | 2017年

关键词：

the self-adaptive sliding mode control; genetic algorithm; optimization;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The self-adaptive sliding mode position controller based on genetic algorithm optimization is designed for the servo motor drive system. Firstly, the self-adaptive sliding mode position controller is researched to estimate the magnitude of the unknown disturbance in the perturbed system. Then, the adaptive genetic algorithm is used to optimize the ideal adaptive parameters and switching parameters. In the end of the paper, several simulation experiments are carried out to test the performance of the system. The results show that the adaptive genetic algorithm has better control performance and position tracking response for the system parameter variation and external load disturbance.

引用

页码：821 / 825

页数：5

共 5 条

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[5] Zhang Shi-hua, 2004, Proceedings of the CSEE, V24, P210

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