Title :
The ship controller design based on RBF
Author :
Sui, Jianghua ; Zhang, Wenxiao ; Yu, Gongzhi
Author_Institution :
Mech. Coll., Dalian Ocean Univ., Dalian, China
Abstract :
A novel approach is promoted for fuzzy neural ship controllers. A 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 satisfied results have been obtained.
Keywords :
control system synthesis; fuzzy control; genetic algorithms; neurocontrollers; nonlinear systems; ships; time-varying systems; uncertain systems; GA optimization; RBF neural network; Simulink tools; fuzzy neural ship controller design; nonlinearity factors; time varying factors; uncertain factors; union-rule configuration; Adaptation model; Artificial neural networks; Gallium; Marine vehicles; Niobium; Optimization; Radial basis function networks; RBF network; fuzzy control; genetic algorithm; ship control; simulation test;
Conference_Titel :
Management Science and Industrial Engineering (MSIE), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4244-8383-9
DOI :
10.1109/MSIE.2011.5707663
