DocumentCode :
2262174
Title :
Fuzzy system identification using rule-based models
Author :
Shaout, A.K. ; McDonough, J.T., III
Author_Institution :
Michigan Univ., Dearborn, MI, USA
fYear :
1993
fDate :
16-18 Aug 1993
Firstpage :
510
Abstract :
The purpose of the paper was to examine the methods used to develop fuzzy models of SISO systems which may be thought of as “rule-based” using non-recursive techniques. First, we look at the mathematical concepts used to develop the models. Second, special constraints used in the creation of the fuzzy models are specified. Third, fuzzy models of a simple linear system are developed. The models are used to determine the effects of incorrect or overparameterization on the effects of the model performance. Finally, fuzzy models of a simple non-linear system are developed and their performance examined
Keywords :
fuzzy control; fuzzy systems; identification; knowledge based systems; linear systems; nonlinear systems; SISO systems; fuzzy system identification; linear system; model performance; nonlinear system; nonrecursive techniques; overparameterization; rule-based models; Biological system modeling; Control system synthesis; Equations; Fuzzy sets; Fuzzy systems; Linear systems; Mathematical model; Predictive models; System testing; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1993., Proceedings of the 36th Midwest Symposium on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-1760-2
Type :
conf
DOI :
10.1109/MWSCAS.1993.343008
Filename :
343008
Link To Document :
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