一种基于模糊神经网络的非线性系统模型辨识方法

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Abstract This paper presents a model identification approach of nonlinear-systems. Through structure identification (learning) and parameter identification (learning), a fuzzy neural network is constructed. Having adjusted the weights of the fuzzy neural network, a precise fuzzy model is obtained. Finally, the effectiveness of the proposed technique is confirmed by the simulation results of two nonlinear systems.

Key words： Fuzzy neural networks Structure identification Parameter identification System identification

Received: 12 January 2000

PACS:	TP391.4
	TN-052

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	Li Ying
	Bai Bendu
	Jiao Licheng

Cite this article:

Li Ying,Bai Bendu,Jiao Licheng. A model identification approach of nonlinear-systems based on fuzzy neural networks[J]. , 2002, 24(3): 355-360 .

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http://jeit.ie.ac.cn/EN/ OR http://jeit.ie.ac.cn/EN/Y2002/V24/I3/355

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