Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30854
Title: A fuzzy neural network based on fuzzy hierarchy error approach
Authors: Wu, A
Tam, PKS
Keywords: Adaptive control
Error approach
Fuzzy controller
Fuzzy neural network
Learning algorithm
Issue Date: 2000
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on fuzzy systems, 2000, v. 8, no. 6, p. 808-816 How to cite?
Journal: IEEE transactions on fuzzy systems 
Abstract: This letter presents a novel fuzzy neural network, which is composed of an antecedent network and a consequent network. The antecedent network matches the premises of the fuzzy rules and the consequent network implements the consequences of the rules. In the network learning and training phase, a concise and effective algorithm based on the fuzzy hierarchy error approach (FHEA) is proposed to update the parameters of the network. This algorithm is simple to implement and it does not require as many calculations as some other classic neural network learning algorithms. A model reference adaptive control structure incorporating the proposed fuzzy neural network is studied. Simulation results of a cart-pole balancing system demonstrate the effectiveness of proposed method.
URI: http://hdl.handle.net/10397/30854
ISSN: 1063-6706 (print)
1941-0034 (online)
DOI: 10.1109/91.890349
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