Direct adaptive control via decomposed fuzzy petri net

Shun Feng Su, Ming Chang Chen, Yi Hsing Chien, Wei Yen Wang, Kuo Kai Shyu

Research output: Contribution to journalConference article

Abstract

This paper presents a novel direct adaptive controller design via decomposed fuzzy Petri net to solve the control tracking problem. The controller combines decomposed fuzzy system (DFS) and Petri net to achieve good performance with less computation time. In the DFS structure, fuzzy variables are decomposed into several layers. DFS has been shown to have fast learning capability but with a complicated system structure. In this study, Petri net is employed to form a mechanism in constructing meaningful component fuzzy systems in the DFS so that the number of fuzzy components can be dramatically reduced without significantly degrading the modeling performance. Finally, the effectiveness of the proposed controller scheme is verified by simulation results.

Original languageEnglish
Article number6974535
Pages (from-to)3873-3877
Number of pages5
JournalConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2014-January
Issue numberJanuary
DOIs
Publication statusPublished - 2014
Event2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014 - San Diego, United States
Duration: 2014 Oct 52014 Oct 8

Keywords

  • Adaptive control
  • Decomposed fuzzy system
  • Fuzzy petri net

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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