Adaptive dynamic surface control for uncertain nonlinear systems with interval type-2 fuzzy neural networks

Yeong Hwa Chang, Wei Shou Chan

Research output: Contribution to journalJournal Article peer-review

88 Scopus citations

Abstract

This paper presents a new robust adaptive control method for a class of nonlinear systems subject to uncertainties. The proposed approach is based on an adaptive dynamic surface control, where the system uncertainties are approximately modeled by interval type-2 fuzzy neural networks. In this paper, the robust stability of the closed-loop system is guaranteed by the Lyapunov theorem, and all error signals are shown to be uniformly ultimately bounded. In addition to simulations, the proposed method is applied to a real ball-and-beam system for performance evaluations. To highlight the system robustness, different initial settings of ball-and-beam parameters are considered. Simulation and experimental results indicate that the proposed control scheme has superior responses, compared to conventional dynamic surface control.

Original languageEnglish
Article number6506097
Pages (from-to)293-304
Number of pages12
JournalIEEE Transactions on Cybernetics
Volume44
Issue number2
DOIs
StatePublished - 02 2014

Keywords

  • Ball-and-beam system
  • dynamic surface control
  • interval type-2 fuzzy neural network

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