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Title of Journal: Neural Comput Applic

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Abbravation: Neural Computing and Applications

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Springer-Verlag

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DOI

10.1002/scin.5591510101

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1433-3058

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Supervisory recurrent fuzzy neural network control

Authors: YiJen Mon ChihMin Lin
Publish Date: 2012/08/02
Volume: 21, Issue: 8, Pages: 2163-2169
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Abstract

This paper develops an intelligent method called supervisory recurrent fuzzy neural network SRFNN control to deal with the vehicle collision avoidance system VCAS which is an uncertain nonlinear modelfree system This SRFNN control system is composed of a recurrent fuzzy neural network RFNN controller and a supervisory controller The RFNN controller is investigated to mimic an ideal controller and the supervisory controller is designed to compensate for the approximation error between the RFNN controller and the ideal controller This SRFNN control is employed to keep the VCAS within a safety range to avoid traffic accidences The simulation results show the performance and effectiveness of the proposed control system are better than that obtained by formal formulabased control

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