Fuzzy identification of nonlinear systems

Cem T. Ayday*, Ibrahim Eksin

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6 Atıf (Scopus)

Özet

This paper presents a mathematical way of building a fuzzy model of any nonlinear system. The fuzzy implications of the system model and the least square identification method have been used to describe the nonlinear systems under study. The phase plane on which the nonlinear system is to be represented has been partitioned into fuzzy subregions and a linear fuzzy system model has been identified for each region. Then it has been observed that the overall system behavior has been characterized quite satisfactorily by using this partitioned fuzzy modelling.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıPlenary Session, Emerging Technologies, and Factory Automation
Editörler Anon
YayınlayanPubl by IEEE
Sayfalar289-292
Sayfa sayısı4
ISBN (Basılı)0780308913
Yayın durumuYayınlandı - 1993
EtkinlikProceedings of the 19th International Conference on Industrial Electronics, Control and Instrumentation - Maui, Hawaii, USA
Süre: 15 Kas 199318 Kas 1993

Yayın serisi

AdıIECON Proceedings (Industrial Electronics Conference)
Hacim1

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???event.eventtypes.event.conference???Proceedings of the 19th International Conference on Industrial Electronics, Control and Instrumentation
ŞehirMaui, Hawaii, USA
Periyot15/11/9318/11/93

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