DocumentCode
1661175
Title
Takagi-Sugeno fuzzy models within orthonormal basis function framework and their application to process control
Author
Campello, R.J.G.B. ; Amaral, W.C.
Author_Institution
Dept. of Comput. Eng. & Ind. Autom., State Univ. of Campinas (Unicamp), Brazil
Volume
2
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
1399
Lastpage
1404
Abstract
Fuzzy models within orthonormal basis function framework (OBF Fuzzy Models) have been introduced in previous works and shown to be a very promising approach to the areas of non-linear system identification and control since they exhibit several advantages over those dynamic model topologies usually adopted in the literature. In the present paper, it is demonstrated that the OBF Takagi-Sugeno fuzzy models previously introduced by the authors are particular realizations of a more general and interpretable formulation presented here, while being able to approximate to desired accuracy a wide class of non-linear dynamic systems. In addition, a predictive control scheme based on the linearization of these models is applied to the control of a polymerization reactor
Keywords
fuzzy logic; mean square error methods; nonlinear dynamical systems; predictive control; process control; radial basis function networks; Takagi-Sugeno fuzzy models; dynamic model topologies; nonlinear dynamic systems; nonlinear system identification; orthonormal basis function framework; polymerization reactor; predictive control scheme; process control; Control system synthesis; Fuzzy control; Fuzzy systems; Nonlinear control systems; Nonlinear dynamical systems; Predictive control; Predictive models; System identification; Takagi-Sugeno model; Topology;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/FUZZ.2002.1006709
Filename
1006709
Link To Document