Title :
Guaranteed-cost fuzzy filter design for a class of nonlinear discrete-time uncertain systems
Author :
Tseng, Chung-Shi ; Chen, Bor-Sen ; Lee, Bore-kuen
Author_Institution :
Dept. of Electr. Eng., Ming Hsin Univ. of Sci. Technol., Hsin Feng, Taiwan
Abstract :
In general, it is a difficult work to design an efficient filter for nonlinear systems. This paper studies fuzzy filtering design for nonlinear discrete-time systems. First, the Takagi and Sugeno fuzzy model is proposed to approximate a nonlinear discrete-time system. Next, based on the fuzzy model, the fuzzy estimation for nonlinear discrete-time systems is studied. Using a suboptimal approach, the minimum variance fuzzy estimation problems are characterized in terms of an eigenvalue problem (EVP) by minimizing the upper bound on the variance of the estimation error. The EVP can be solved very efficiently using convex optimization techniques.
Keywords :
Kalman filters; cost optimal control; discrete time systems; eigenvalues and eigenfunctions; filtering theory; fuzzy systems; linear matrix inequalities; nonlinear control systems; suboptimal control; Kalman filter; Takagi-Sugeno fuzzy model; efficient filter design; eigenvalue problems; guaranteed-cost fuzzy filter design; linear matrix inequalities; minimum variance fuzzy estimation; nonlinear discrete-time uncertain systems; optimal filters; robust filtering; suboptimal approach; upper bound; Design engineering; Estimation error; Filtering; Fuzzy systems; Nonlinear filters; Nonlinear systems; Robustness; State estimation; Uncertain systems; Upper bound;
Conference_Titel :
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN :
0-7803-7810-5
DOI :
10.1109/FUZZ.2003.1209405
