A supervisory fuzzy neural network control system for tracking periodic inputs

Faa Jeng Lin, Wen Jyi Hwang, Rong Jong Wai

研究成果: 雜誌貢獻文章同行評審

187 引文 斯高帕斯(Scopus)

摘要

A supervisory fuzzy neural network (FNN) control system is designed to track periodic reference inputs in this study. The control system is composed of a permanent magnet (PM) synchronous servo motor drive with a supervisory FNN position controller. The supervisory FNN controller comprises a supervisory controller, which is designed to stabilize the system states around a defined bound region and an FNN sliding-mode controller, which combines the advantages of the sliding-mode control with robust characteristics and the FNN with on-line learning ability. The theoretical and stability analyses of the supervisory FNN controller are discussed in detail. Simulation and experimental results show that the proposed control system is robust with regard to plant parameter variations and external load disturbance. Moreover, the advantages of the proposed control system are indicated in comparison with the sliding-mode control system.

原文英語
頁(從 - 到)41-52
頁數12
期刊IEEE Transactions on Fuzzy Systems
7
發行號1
DOIs
出版狀態已發佈 - 1999 十二月 1

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

指紋 深入研究「A supervisory fuzzy neural network control system for tracking periodic inputs」主題。共同形成了獨特的指紋。

引用此