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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Guoqing Xia Shuning Zhang Yuanhui Wang Zhaodong Tang |
| Copyright Year | 2010 |
| Description | Author affiliation: College of Automation, Harbin Engineering University, 150001, China (Guoqing Xia; Shuning Zhang; Yuanhui Wang; Zhaodong Tang) |
| 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. |
| Starting Page | 1513 |
| Ending Page | 1517 |
| File Size | 265258 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424459582 |
| e-ISBN | 9781424459612 |
| DOI | 10.1109/ICNC.2010.5582652 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-08-10 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | RBF neural network component multimodal control DSRV Oceans Simulation Adaptation model Artificial neural networks Mathematical model dynamic positioning system Underwater vehicles Vehicles |
| Content Type | Text |
| Resource Type | Article |
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