DocumentCode :
1752781
Title :
Robust Neural Network and Its Application to Course-keeping for Ships
Author :
Zhang, Xianku ; Lu, Xiaofei ; GUO, Chen
Author_Institution :
Lab. of Simulation & Control of Navigation Syst., Dalian Maritime Univ.
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
2647
Lastpage :
2650
Abstract :
A feed-forward network with seven layers was designed and trained to acquire an open loop controller of course-keeping for ships. The NNC controller with five inputs and one output could follow the tacks of typical course curve with good precision, then a closed loop control system was constructed using closed loop gain shaping algorithm. The robustness of the system is improved because the control strategy connects the adaptability and nonlinear mapping of neural network with robustness of closed loop gain shaping algorithm. This method has the advantages of simple design procedure and obvious physical sense
Keywords :
adaptive control; closed loop systems; control system synthesis; feedforward neural nets; navigation; neurocontrollers; nonlinear control systems; open loop systems; position control; robust control; ships; adaptability; closed loop control system; closed loop gain shaping; control design; feedforward network; neural network; nonlinear mapping; open loop controller; robustness; ship course keeping; Control system synthesis; Control systems; Feedforward systems; Marine vehicles; Navigation; Neural networks; Open loop systems; Robust control; Robustness; Shape control; closed loop gain shaping; course-keeping; neural network; robust controller;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1712842
Filename :
1712842
Link To Document :
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