[1]YANG Di,GUO Chen,ZHU Yuhua,et al.Neural network adaptive path tracking control for underactuated ships[J].CAAI Transactions on Intelligent Systems,2018,13(2):254-260.[doi:10.11992/tis.201611011]
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CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
13
Number of periods:
2018 2
Page number:
254-260
Column:
学术论文—智能系统
Public date:
2018-04-15
- Title:
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Neural network adaptive path tracking control for underactuated ships
- Author(s):
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YANG Di1; GUO Chen2; ZHU Yuhua1; FU Si1
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1. College of Chemical Process Atomation, Shenyang University of Technology, Liaoyang 111003, China;
2. Institute of Ship Automation and Simulator, Dalian Maritime University, Dalian 116026, China
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- Keywords:
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underactuated ship; parameter uncertainties; backstepping; adaptive control; neural networks; path following; Lyapunov function; ultimately uniform boundedness
- CLC:
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TP391
- DOI:
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10.11992/tis.201611011
- Abstract:
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Considering path-following problems of underactuated ships with parameter uncertainties, the nerve network technology was combined with the backstepping method for proposing a stable nerve-network adaptive control method. Firstly, based on kinematics error equations and linear transformation, auxiliary surge velocity and heading angle were determined; then the nerve network approximation technology was utilized to compensate for any uncertainties in the model, an adaptive control law was designed, so as to make actual surge velocity and heading angle converge to the auxiliary values respectively. By using the Lyapunov function, it was proved that the ultimately uniform boundedness of the error signals in the closed-loop path following system of ship. Numerical simulation results show that, the designed law can force underactuated ship to follow curve and straight path, it has strong robustness.