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

 

Author: Feisiang Tay; Zhihong Man; Zhenwei Cao; Suiyang Khoo; Chee Pin Tan

 

Addresses:
Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, P.O. Box 218, Hawthorn, Victoria, 3122, Australia.
Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, P.O. Box 218, Hawthorn, Victoria, 3122, Australia.
Faculty of Engineering and Industrial Sciences, Swinburne University of Technology, P.O. Box 218, Hawthorn, Victoria, 3122, Australia.
Faculty of Science and Technology, Deakin University, Pigdons Road, Geelong Victoria 3217, Australia.
Research and Research Training, Monash University, Jalan Lagoon Selatan, Bandar Sunway, 46150, Selangor Darul Ehsan, Malaysia

 

Journal: Int. J. of Modelling, Identification and Control, 2012 Vol.16, No.4, pp.317 - 326

 

Abstract: 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.

 

Keywords: Takagi-Sugeno models; T-S models; sliding mode control; learning control; chattering; Lyapunov stability; Lipschitz condition; fuzzy modelling; SISO complex systems; uncertainty; dynamical systems; uncertain system dynamics; simulation; inverted pendulum cart.

 

DOI: http://dx.doi.org/10.1504/IJMIC.2012.048264

 

Available online 25 Jul 2012

 

 

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