DocumentCode
2539737
Title
Robust quadratic optimal control of uncertain TS-fuzzy-model-based dynamic systems
Author
Ho, Wen-Hsien ; Tsai, Jinn-Tsong ; Liu, Tung-Kuan ; Chou, Jyh-Horng
Author_Institution
Kaohsiung Med. Univ., Kaohsiung
fYear
2007
fDate
7-10 Oct. 2007
Firstpage
3087
Lastpage
3089
Abstract
This paper considers the design problem of the robust quadratic-optimal parallel-distributed-compensation (PDC) controllers for the Takagi-Sugeno (TS) fuzzy-model- based control systems with both elemental parametric uncertainties and norm-bounded approximation error. An integrative method, which complementarily fuses the robust stabilizability condition, the orthogonal-functions approach (OFA) and the hybrid Taguchi-genetic algorithm (HTGA), is presented in this paper to design the robust quadratic-optimal PDC controllers, in which the robust stabilizability condition is proposed in terms of linear matrix inequalities (LMIs).
Keywords
approximation theory; compensation; control system synthesis; distributed control; fuzzy control; genetic algorithms; linear matrix inequalities; optimal control; robust control; uncertain systems; design problem; dynamic systems; elemental parametric uncertainties; hybrid Taguchi-genetic algorithm; integrative method; linear matrix inequalities; norm-bounded approximation error; orthogonal-functions approach; parallel-distributed-compensation controllers; robust quadratic optimal control; robust stabilizability condition; uncertain TS-fuzzy-model; Algorithm design and analysis; Approximation error; Control systems; Fuzzy control; Fuzzy systems; Nonlinear control systems; Nonlinear dynamical systems; Optimal control; Robust control; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on
Conference_Location
Montreal, Que.
Print_ISBN
978-1-4244-0990-7
Electronic_ISBN
978-1-4244-0991-4
Type
conf
DOI
10.1109/ICSMC.2007.4413629
Filename
4413629
Link To Document