Title :
Optimal nonlinear filters based on the Takagi-Sugeno fuzzy model
Author :
Kiriakidis, Kiriakos
Author_Institution :
United States Naval Acad., Annapolis, MD, USA
fDate :
6/24/1905 12:00:00 AM
Abstract :
Treats the estimation of the output of interest for a class of nonlinear plants that admit the Takagi-Sugeno (TS) fuzzy model. Based on such a model, we propose the synthesis of a filter whose estimation error is less than a prescribed fraction of the disturbance, by measure of the Euclidean norm. We also address the optimization of the filter´s performance
Keywords :
filtering theory; fuzzy set theory; matrix algebra; nonlinear systems; state estimation; Euclidean norm; Takagi-Sugeno fuzzy model; estimation; nonlinear plants; optimal nonlinear filters; performance optimization; Estimation error; Filtering; Fuzzy systems; Linear matrix inequalities; Nonlinear filters; Nonlinear systems; Observers; State estimation; Systems engineering and theory; Takagi-Sugeno model;
Conference_Titel :
Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7280-8
DOI :
10.1109/FUZZ.2002.1005009
