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A Genetically Optimized Fuzzy Neural Network for Ship Controllers

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3 Author(s)
Jianghua Sui ; Marine Eng. Coll., Dalian Maritime Univ. ; Yejin Lin ; Guang Ren

A novel approach has been promoted for fuzzy neural ship controllers. An RBF neural network and GA optimization are employed in a fuzzy neural controller to deal with the nonlinearity, time varying and uncertain factors. Utilizing the designed network to substitute the conventional fuzzy inference, the rule base and membership functions can be auto-adjusted by GA optimization. The parameters of neural network can be decreased by using union-rule configuration in the hidden layer of the network. The performance of controller is evaluated by the system simulation conducted with Simulink tools, by which satisfactory results were obtained

Published in:

Mechatronics and Automation, Proceedings of the 2006 IEEE International Conference on

Date of Conference:

25-28 June 2006