Identification and fuzzy controller design for nonlinear uncertain systems with input time-delay

Ching Hung Lee*, Hung Tai Cheng

*Corresponding author for this work

Research output: Contribution to journalArticle

18 Scopus citations

Abstract

This paper considers the identification and fuzzy controller design for nonlinear uncertain systems in presence of unknown input time-delay. Firstly, a time-delay Takagi-Sugeno-Kang (TSK) type fuzzy neural system (TDFN) is proposed to identify a class of nonlinear input time-delay systems. The in-put-output signals of nonlinear systems are used to identify the system dynamics and unknown time-delay, and then construct the system in the form TSK-fuzzy time-delay model. Each fuzzy rule has a corresponding linear system with an input time-delay as the consequent part. Based on parallel distribution compensation (PDC) approach, the Smith predictor compensation and dominate pole assignment tech-nique are then adopted to design the fuzzy PID con-troller. Several simulations are shown to demonstrate the effectiveness and control performance of the proposed approach.

Original languageEnglish
Pages (from-to)73-86
Number of pages14
JournalInternational Journal of Fuzzy Systems
Volume11
Issue number2
StatePublished - Jun 2009

Keywords

  • Neural networks
  • Nonlinear control
  • PID controller
  • Smith predictor
  • Time-delay systems
  • TSK type fuzzy model

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