Observer-based adaptive FNN control of robot manipulators: PSO-SA self adjust membership approach

Shih Kai-Shiuan, Li S. Tzuu-Hseng, Tsai Shun-Hung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a novel observer-based adaptive fuzzy-neural network (FNN) control scheme for robotic systems is proposed for tracking performance and to suppress the effects caused by uncertainties, and disturbances. A PSO-SA based adaptive FNN system is used to approximate an unknown system from the manipulation of the model following tracking errors. The proposed scheme uses an observer, which allows for identifying the state of an unknown state in the system, simultaneously. It is shown that the proposed control scheme can guarantee the better tracking performance and suppress internal uncertainties or external disturbance. Simulations are given to show the validity and confirm the performance of the proposed scheme.

Original languageEnglish
Title of host publicationFUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings
Pages1852-1859
Number of pages8
DOIs
Publication statusPublished - 2011 Sep 27
Event2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei, Taiwan
Duration: 2011 Jun 272011 Jun 30

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Other

Other2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
CountryTaiwan
CityTaipei
Period11-06-2711-06-30

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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