Tuning of Servo Drive Controller Based on Boosted Tree Model and Particle Swarm Optimization

Chi Wen Chen, Lien Kai Chang, Yi Ting Liao, Chun Hui Chung, Wei Chih Su, Kuo Shen Chen, Mi Ching Tsai

研究成果: Conference contribution

摘要

This paper presents a gain tuning method for servo drives that combines machine learning model (LightGBM) and optimization algorithm (PSO). The LightGBM model can predict the response characteristics of the servo system under different gain parameters of the servo drive. Then, the PSO will tuning the gain parameters to obtain the best performance. A new performance criterion for evaluating the servo drive is proposed. It consists of several time-domain position response characteristics, such as percentage of overshoot and settling time etc., and the servo drive performance can be optimized by utilizing those characteristics. The experimental result shows that the appropriate gain parameters can be obtained through this proposed AI tuning method.

原文English
主出版物標題23rd International Conference on Electrical Machines and Systems, ICEMS 2020
發行者Institute of Electrical and Electronics Engineers Inc.
頁面107-110
頁數4
ISBN(電子)9784886864192
DOIs
出版狀態Published - 2020 十一月 24
事件23rd International Conference on Electrical Machines and Systems, ICEMS 2020 - Hamamatsu, Japan
持續時間: 2020 十一月 242020 十一月 27

出版系列

名字23rd International Conference on Electrical Machines and Systems, ICEMS 2020

Conference

Conference23rd International Conference on Electrical Machines and Systems, ICEMS 2020
國家/地區Japan
城市Hamamatsu
期間20-11-2420-11-27

All Science Journal Classification (ASJC) codes

  • 能源工程與電力技術
  • 電氣與電子工程
  • 機械工業
  • 安全、風險、可靠性和品質
  • 控制和優化

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