Fuzzy identification using fuzzy neural networks with stable learning algorithms.

Fuzzy identification using fuzzy neural networks with stable learning algorithms.

In general, fuzzy neural networks cannot match nonlinear systems exactly. Unmodeled dynamic leads parameters drift and even instability problem. According to system identification theory, robust modification terms must be included in order to guarantee Lyapunov stability. This paper suggests new lea...

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Detalhes bibliográficos
Publicado no:IEEE Transactions on fuzzy systems 12, 3 (2004).
Autor principal: Wen Yu
Formato: Artigo
Idioma:English
Assuntos:
Lyapunov stability.
Takagi Sugeno Kang system.
Fuzzy neural network.
Fuzzy rules.
Input to state stability.
Learning algorithms.
System identification theory.