DocumentCode
3101503
Title
H∞ output feedback control of discrete-time stochastic T-S fuzzy models with state-dependent noise
Author
Lin, Hsuan-Heng ; Lee, Bore-kuen ; Wu, Chein-Fong
Author_Institution
Dept. of Electr. Eng., Chung Hua Univ., Hsinchu, Taiwan
Volume
6
fYear
2009
fDate
12-15 July 2009
Firstpage
3264
Lastpage
3269
Abstract
In this paper, Hinfin dynamic output feedback control for discrete-time nonlinear stochastic T-S fuzzy model with state-dependent noise is attacked. We consider the fuzzy T-S models has has stochastic uncertainties, i.e., state-dependent noise, in the system matrix, input matrix, and output matrix. First, when the premise variables in the fuzzy plant model are available, an Hinfin fuzzy dynamic output feedback controller, which uses the same premise variables as the T-S fuzzy model, is proposed for regulation of the controlled system to meet the Hinfin control performance specification. Next, when the premise variables for building the fuzzy plant model are not available, a fuzzy Hinfin observer-based state feedback controller, in which the premise variables are the estimated version of the premise variables in the T-S fuzzy model, is proposed. For the two cases, we conduct sufficient conditions described by linear matrix inequalities (LMI) to ensure stability of the closed-loop system. Performance of the proposed fuzzy controller is verified by simulation study.
Keywords
Hinfin control; closed loop systems; discrete time systems; fuzzy control; linear matrix inequalities; nonlinear control systems; observers; stability; state feedback; stochastic systems; uncertain systems; Hinfin control performance specification; Hinfin dynamic output feedback control; closed-loop system stability; controlled system regulation; discrete-time nonlinear stochastic T-S fuzzy model; fuzzy Hinfin observer; fuzzy plant model; linear matrix inequalities; state feedback controller; state-dependent noise; stochastic uncertainties; Control system synthesis; Fuzzy control; Fuzzy systems; Nonlinear dynamical systems; Output feedback; State estimation; State feedback; Stochastic resonance; Stochastic systems; Uncertainty; H∞ ; Output feedback; Stochastic T-S fuzzy model; control;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location
Baoding
Print_ISBN
978-1-4244-3702-3
Electronic_ISBN
978-1-4244-3703-0
Type
conf
DOI
10.1109/ICMLC.2009.5212736
Filename
5212736
Link To Document