LEARNING
Autopilot design for a robotic unmanned surface vehicle
Zhouhua Peng, Yong Tian, Dan Wang, Lu Liu
- 发表年份
- 2015
- 引用次数
- 6
摘要
This paper reports an autopilot design for a robotic unmanned surface vehicle in the control laboratory at DMU. A robust adaptive steering law is developed with the aid of a predictor, a tracking differentiator, neural networks, and a dynamic surface control technique. The developed controller is able to achieve satisfactory performance in the presence of model uncertainties, time-varying ocean disturbances, and measurement noises. Simulation results demonstrate the efficacy of the proposed method.
关键词
AutopilotDifferentiatorControl engineeringControl theory (sociology)Unmanned surface vehicleComputer scienceAttitude controlController (irrigation)Vehicle dynamicsTracking (education)
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