DocumentCode :
2067461
Title :
Study on ship steering based on hybrid intelligent control
Author :
YANG, Guoxun ; GUO, Chen ; Jia, Xinle
Author_Institution :
Lab of Simulation & Control of Navigation Syst., Dalian Maritime Univ., China
Volume :
3
fYear :
2002
fDate :
2002
Firstpage :
2118
Abstract :
Hybrid intelligent technique is used in ship steering control. It can make full use of the advantages of all kinds of intelligent algorithms. This provides an efficient way for the improvement of ship steering control performance. In this paper, genetic algorithm optimization is used in off-line learning period. According to the new definition of fitness function, the optimized result obtained is more suitable to the actual situation. In online learning period, reinforcement learning and neural fuzzy control are integrated. It removes the defect that the conventional hybrid intelligent algorithm learning must be provided with some sample data, and. the ship control quality is effectively improved in the case of appending additional sea state disturbance.
Keywords :
fuzzy control; genetic algorithms; intelligent control; learning (artificial intelligence); neurocontrollers; position control; ships; fitness function; fuzzy control; genetic algorithm; hybrid intelligent control; neural control; optimization; reinforcement learning; ship; steering control; Control system synthesis; Fuzzy control; Fuzzy neural networks; Intelligent control; Intelligent robots; Marine vehicles; Navigation; Neural networks; Supervised learning; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2002. Proceedings of the 2002
ISSN :
0743-1619
Print_ISBN :
0-7803-7298-0
Type :
conf
DOI :
10.1109/ACC.2002.1023949
Filename :
1023949
Link To Document :
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