DocumentCode :
1661324
Title :
A robust learning control for SISO nonlinear systems with T-S fuzzy model: C02-robust control
Author :
Fei Siang Tay ; Zhihong Man ; Zhenwei Cao ; Jiong Jin ; Sui Yang Khoo
Author_Institution :
Fac. of Eng. & Ind. Sci., Swinburne Univ. of Technol., Hawthorn, VIC, Australia
fYear :
2012
Firstpage :
492
Lastpage :
497
Abstract :
In this paper, a robust learning control is developed for a class of single input single output (SISO) nonlinear systems with T-S fuzzy model. It is seen that the proposed sliding mode learning control with the powerful Lipshitz-like condition can guarantee the stability, convergence and robustness of the closed-loop system without involving any assumptions on uncertain system dynamics. In addition, the concept that the local system with the maximum membership function dominates the system dynamic behaviours helps to greatly simplify the control system design. It will be further seen that the continuous learning control ensures the advantage of chattering-free that may occur in conventional sliding mode systems. Simulation examples are presented to demonstrate the effectiveness of the proposed learning control through the comparison with the H-infinity control.
Keywords :
H control; closed loop systems; control system synthesis; fuzzy control; learning systems; nonlinear control systems; robust control; variable structure systems; H-infinity control; Lipshitz-like condition; SISO nonlinear system; T-S fuzzy mode; closed-loop system; continuous learning control; membership function; robust control; robust learning control; single input single output control; sliding mode learning control; stability; Asymptotic stability; Closed loop systems; Convergence; Delay effects; Mathematical model; Robustness; Stability analysis; Lipschitz condition; Lyapunov stability; T-S fuzzy model; learning control; sliding mode;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4673-1871-6
Electronic_ISBN :
978-1-4673-1870-9
Type :
conf
DOI :
10.1109/ICARCV.2012.6485208
Filename :
6485208
Link To Document :
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