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
fDate :
6/24/1905 12:00:00 AM
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;
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.2002.1006709