Title :
Modeling via on-line clustering and fuzzy support vector machines for nonlinear system
Author :
Tovar, Julio César ; Yu, Wen ; Ortiz, Floriberto ; Mariaca, Carlos Román ; de Jesus Rubio, Jose
Author_Institution :
Eng. Commun. & Electron. Autom. Control Dept., Nat. Inst. Polytech., Mexico City, Mexico
Abstract :
This paper describes a novel non-linear modeling approach by on-line clustering, fuzzy rules and fuzzy support vector machines. Structure identification is realized by on-line clustering method and support vector machines, and the rules are generated automatically. Time-varying learning rates are applied for updating the membership functions of the fuzzy rules. Finally, tue upper bounds of modeling errors are proven.
Keywords :
fuzzy set theory; fuzzy systems; learning (artificial intelligence); learning systems; nonlinear systems; pattern clustering; support vector machines; fuzzy membership function; fuzzy rules; fuzzy support vector machine; nonlinear modeling approach; nonlinear system; online clustering; rule generation; structure identification; time-varying learning rate; Engines; Fuzzy systems; Kernel; Nonlinear systems; Support vector machines; Training; Vectors;
Conference_Titel :
Decision and Control and European Control Conference (CDC-ECC), 2011 50th IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-61284-800-6
Electronic_ISBN :
0743-1546
DOI :
10.1109/CDC.2011.6161420
