A supervisory fuzzy neural network control system for tracking periodic inputs

Faa Jeng Lin, Wen Jyi Hwang, Rong Jong Wai

Research output: Contribution to journalArticle

185 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)41-52
Number of pages12
JournalIEEE Transactions on Fuzzy Systems
Volume7
Issue number1
DOIs
Publication statusPublished - 1999 Dec 1

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Neural Network Control
Fuzzy neural networks
Fuzzy Neural Network
Control System
Control systems
Controller
Controllers
Sliding mode control
Sliding Mode Control
Permanent Magnet
Sliding Mode
Permanent magnets
Disturbance
Experimental Results
Simulation

Keywords

  • Fuzzy neural network
  • PM synchronous servo motor
  • Periodic inputs
  • Supervisory control

ASJC Scopus subject areas

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

Cite this

A supervisory fuzzy neural network control system for tracking periodic inputs. / Lin, Faa Jeng; Hwang, Wen Jyi; Wai, Rong Jong.

In: IEEE Transactions on Fuzzy Systems, Vol. 7, No. 1, 01.12.1999, p. 41-52.

Research output: Contribution to journalArticle

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