控制理论(社会学)
人工神经网络
稳健性(进化)
自适应控制
计算机科学
强化学习
补偿(心理学)
控制工程
弹道
理论(学习稳定性)
控制(管理)
工程类
人工智能
机器学习
心理学
生物化学
化学
物理
天文
精神分析
基因
作者
Rongxin Cui,Chenguang Yang,Yang Li,Sanjay Sharma
出处
期刊:IEEE transactions on systems, man, and cybernetics
[Institute of Electrical and Electronics Engineers]
日期:2017-01-10
卷期号:47 (6): 1019-1029
被引量:434
标识
DOI:10.1109/tsmc.2016.2645699
摘要
In this paper, we investigate the trajectory tracking problem for a fully actuated autonomous underwater vehicle (AUV) that moves in the horizontal plane. External disturbances, control input nonlinearities and model uncertainties are considered in our control design. Based on the dynamics model derived in the discrete-time domain, two neural networks (NNs), including a critic and an action NN, are integrated into our adaptive control design. The critic NN is introduced to evaluate the long-time performance of the designed control in the current time step, and the action NN is used to compensate for the unknown dynamics. To eliminate the AUV's control input nonlinearities, a compensation item is also designed in the adaptive control. Rigorous theoretical analysis is performed to prove the stability and performance of the proposed control law. Moreover, the robustness and effectiveness of the proposed control method are tested and validated through extensive numerical simulation results.
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