DocumentCode :
527421
Title :
Adaptive multimodal PID controller based on RBF neural network for A DSRV
Author :
Xia, Guoqing ; Zhang, Shuning ; Wang, Yuanhui ; Tang, Zhaodong
Author_Institution :
Coll. of Autom., Harbin Eng. Univ., Harbin, China
Volume :
3
fYear :
2010
fDate :
10-12 Aug. 2010
Firstpage :
1513
Lastpage :
1517
Abstract :
Dynamic positioning system of deep submergence rescue vehicle using conventional PID control can get a good performance in the fixed ocean current. But it is very difficult to achieve the control requirements in the mutative ocean current. In this paper, a novel control algorithm that is integrated RBF neural network with multimodal PID controller is designed, which can automatically adjust the PID parameters when the deep submergence rescue vehicle suffers disturbances of variational ocean current. Simulation shows that this control method can achieve the quite ideal control effect under the mutative ocean current.
Keywords :
adaptive control; control system synthesis; emergency services; marine control; radial basis function networks; three-term control; underwater vehicles; DSRV; RBF neural network; adaptive multimodal PID controller; deep submergence rescue vehicle; dynamic positioning system; mutative ocean current; Adaptation model; Artificial neural networks; Mathematical model; Oceans; Simulation; Underwater vehicles; Vehicles; DSRV; RBF neural network; component; dynamic positioning system; multimodal control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
Type :
conf
DOI :
10.1109/ICNC.2010.5582652
Filename :
5582652
Link To Document :
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