Chaotic Newton-raphson optimization based predictive control for permanent magnet synchronous motor systems with long-delay

Bing-Fei Wu*, Chun Hsien Lin

*此作品的通信作者

研究成果: Conference contribution同行評審

3 引文 斯高帕斯(Scopus)

摘要

A Tent-map chaotic Newton-Raphson optimization based neural network predictive control (TCNR-NPC) is developed to apply to the long-delay permanent magnet synchronous motor (PMSM) system in this paper. Due to a nonlinear model utilized in the predictive controller, nonlinear optimization methods turn into an important issue. To overcome the shortcoming of the conventional nonlinear programming on the initial condition sensitivity and maintain the accuracy of optimal solution, chaos optimization algorithm (COA) and Newton-Raphson (NR) are combined. With the comparison of COA and NR based optimization methods, our approach, the Tent-map chaotic Newton-Raphson (TCNR) optimization, is easier to reach the global optimum, thus, it would be employed in neural network predictive control. It is found that TCNR-NPC has a better performance than those of GPC, modified GPC, adaptive extended PSO based NPC, and PSO based PI controllers in real experiments.

原文English
主出版物標題Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
發行者Institute of Electrical and Electronics Engineers Inc.
頁面382-387
頁數6
ISBN(電子)9781479986965
DOIs
出版狀態Published - 12 一月 2016
事件IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 - Kowloon Tong, Hong Kong
持續時間: 9 十月 201512 十月 2015

出版系列

名字Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015

Conference

ConferenceIEEE International Conference on Systems, Man, and Cybernetics, SMC 2015
國家/地區Hong Kong
城市Kowloon Tong
期間9/10/1512/10/15

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