Title :
Simultaneous Linear Control for Non-linear Uncertain Systems Described by Takagi-Sugeno Fuzzy Model
Author :
Shuxiang, Guo ; Youxian, Li
Author_Institution :
Coll. of Sci., Air Force Eng. Univ., Xi´´an, China
fDate :
July 31 2012-Aug. 2 2012
Abstract :
Takagi-Sugeno (T-S) fuzzy model is a system described by a set of fuzzy if-then rules which give local linear representations of the underlying nonlinear system. Usually, a fuzzy control law is constructed by a set of controllers for each local linear representation to carry out the control of a T-S fuzzy system. While, simultaneous control addresses the stability and performance of multiple plants under a single feedback controller. In this paper, simultaneous linear control for nonlinear uncertain systems described by general T-S fuzzy model is considered. A procedure for simultaneous control of T-S fuzzy systems with parametric uncertainties is presented, by which robust reliability method is adopted to deal with uncertainties. Simultaneously linear controller design for an uncertain T-S fuzzy system is carried out by solving a problem of robust reliability based optimization, in which, both the robustness with respect to uncertainties and the control cost can be taken into account simultaneously. It is demonstrated by numerical simulation of the chaotic Lorenz system control that the presented method is effective and feasible.
Keywords :
chaos; control system synthesis; fuzzy set theory; nonlinear systems; optimisation; robust control; uncertain systems; T-S fuzzy model; Takagi-Sugeno fuzzy model; chaotic Lorenz system control; fuzzy control law; fuzzy if-then rules; linear controller design; local linear representations; nonlinear uncertain systems; numerical simulation; parametric uncertainties; robust reliability based optimization; robust reliability method; simultaneous linear control; single feedback controller; stability; Fuzzy systems; Linear matrix inequalities; Nonlinear systems; Robustness; Uncertain systems; Uncertainty; Linear Matrix Inequality; Robust Control; Robust Reliability; Simultaneous Control; T-S Fuzzy System;
Conference_Titel :
Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on
Conference_Location :
GuiLin
Print_ISBN :
978-1-4673-2217-1
DOI :
10.1109/ICDMA.2012.183