Sliding mode-like learning control for SISO complex systems with T-S fuzzy models

Feisiang Tay, Zhihong Man, Zhenwei Cao, Suiyang Khoo, Chee Pin Tan

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5 Citations (Scopus)


In this paper, a sliding mode-like learning control scheme is developed for a class of single input single output (SISO) complex systems. First, the Takagi-Sugeno (T-S) fuzzy modelling technique is employed to model the uncertain complex dynamical systems. Second, a sliding mode-like learning control is designed to drive the sliding variable to converge to the sliding surface, and the system states can then asymptotically converge to zero on the sliding surface. The advantages of this scheme are that: 1 the information about the uncertain system dynamics and the system model structure is not required for the design of the learning controller 2 the closed-loop system behaves with a strong robustness with respect to uncertainties 3 the control input is chattering-free. The sufficient conditions for the sliding mode-like learning control to stabilise the global fuzzy model are discussed in detail. A simulation example for the control of an inverted pendulum cart is presented to demonstrate the effectiveness of the proposed control scheme.

Original languageEnglish
Pages (from-to)317-326
Number of pages10
JournalInternational Journal of Modelling, Identification and Control
Issue number4
Publication statusPublished - Jul 2012


  • Chattering
  • Learning control
  • Lipschitz condition
  • Lyapunov stability
  • Sliding mode
  • T-S
  • Takagi-Sugeno
  • Takagi-Sugeno fuzzy model

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