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Global sliding mode based adaptive neural network path following control for underactuated surface vessels with uncertain dynamics

机译:基于全局滑模的自适应神经网络路径跟随控制不确定动力学水下航行器

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An adaptive neural network (NN) control scheme is proposed for path following control of underactuated surface vessels with only the surge and the yaw moment available, despite the presence of uncertain parameters and unstructured uncertainties including exogenous disturbances and measurement noise, etc. The control scheme is developed by integrating an NN approach and the adaptive implementation of the global sliding mode control. A global sliding mode control approach is developed to provide a framework for ensuring the existence of a sliding mode throughout the entire response, and can force the system state to be within the state region in which the NN is used when the system goes out of NNs control. Based on the Lyapunov stability theory, the uniform ultimate boundedness of the following error is proved. Numerical simulation results are provided to illustrate the effectiveness of the proposed controller and the accuracy of stability analysis.
机译:提出了一种自适应神经网络(NN)控制方案,该方案可对欠驱动的水面船只进行路径跟踪控制,尽管存在不确定的参数和非结构化的不确定性(包括外来干扰和测量噪声等),但仅能获得浪涌和偏航力矩。通过集成NN方法和全局滑模控制的自适应实现来开发。开发了一种全局滑模控制方法,以提供一个框架来确保在整个响应中都存在滑模,并且可以在系统退出NN时强制系统状态位于使用NN的状态区域内控制。基于李雅普诺夫稳定性理论,证明了跟随误差的一致最终有界性。数值仿真结果说明了所提出控制器的有效性和稳定性分析的准确性。

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