Adaptive neural network output-feedback tracking control for switched nonlinear ship maneuvering systems with time delays under arbitrary switching

Zhenhua Li, Xiangxuan Ren, Botao Dong, Hong Chen, W. Zhang
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Abstract

This paper focuses on the tracking control problem for switched nonlinear ship maneuvering time-delay systems with only a heading angle available by adaptive neural network (NN) output feedback. Using the backstepping method, an adaptive NN control mechanism is designed to solve the problem cooperated with the state observer. The uncertain terms of the system are approximated by NNs, and the state observer is designed to estimate the yaw rate and rudder angle. The unknown time delays are overcome by exploiting the common Lyapunov-Krasovskii functionals (CLKFs). Combined with error transformation, the proposed control method guarantees that i) all of the signals for the system are semi-global uniformly ultimately boundedness (SGUUB) under arbitrary switching; and, ii) the tracking error of system output keeps within a small neighborhood around the origin. The results of simulation results are shown to demonstrate the feasibility of the control strategy.
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任意切换非线性时滞船舶机动系统的自适应神经网络输出反馈跟踪控制
本文研究了基于自适应神经网络输出反馈的只有一个航向角的切换非线性船舶机动时滞系统的跟踪控制问题。采用反推法,设计了一种与状态观测器配合的自适应神经网络控制机制。利用神经网络对系统的不确定项进行逼近,并设计状态观测器来估计横摆角速度和舵角。利用常见的Lyapunov-Krasovskii泛函(CLKFs)克服了未知的时间延迟。该控制方法结合误差变换,保证了在任意切换情况下系统的所有信号都是半全局一致最终有界的;ii)系统输出的跟踪误差保持在原点附近的小邻域内。仿真结果验证了控制策略的可行性。
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