DocumentCode :
1566815
Title :
SA-RL Algorithm Based Ship Steering Controller
Author :
Ye, Guang ; Guo, Chen
Author_Institution :
Autom. & Elec. Eng. Coll., Dalian Maritime Univ.
Volume :
3
fYear :
2005
Firstpage :
1780
Lastpage :
1785
Abstract :
Based on simulated annealing (SA) and reinforcement learning (RL) algorithm, a hybrid intelligent controller is proposed to ship steering. The SA algorithm is a powerful way to solve hard combinatorial optimization problems, which is used to adjust the parameters of the controller in this paper. The RL algorithm shows its particular superiority in ship steering, which just needs simple fuzzy information. With the advantages of the two algorithms, the controller can overcome the influence of the wind, wave and flow, the limitation that data are not exactly accurate. At last, the results of the simulation show that the ship course can be properly controlled when changeable wind, wave, and measure error exists
Keywords :
combinatorial mathematics; fuzzy control; intelligent control; learning (artificial intelligence); ships; simulated annealing; steering systems; hard combinatorial optimization problem; hybrid intelligent control; reinforcement learning; ship steering control; simulated annealing; Automatic control; Automation; Computer networks; Educational institutions; Fuzzy systems; Inference algorithms; Learning; Marine vehicles; Neural networks; Simulated annealing; Reinforcement Learning; Ship Steering Control; Simulated Annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9422-4
Type :
conf
DOI :
10.1109/ICNNB.2005.1614972
Filename :
1614972
Link To Document :
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