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PENG Z H , WANG D , WANG W , et al . Containment control of networked autonomous underwater vehicles: a predictor-based neural DSC design [J ] . Isa Transactions , 2015 , 59 : 160 - 171 . DOI: 10.1016/j.isatra.2015.09.018 http://doi.org/10.1016/j.isatra.2015.09.018 This paper investigates the containment control problem of networked autonomous underwater vehicles in the presence of model uncertainty and unknown ocean disturbances. A predictor-based neural dynamic surface control design method is presented to develop the distributed adaptive containment controllers, under which the trajectories of follower vehicles nearly converge to the dynamic convex hull spanned by multiple reference trajectories over a directed network. Prediction errors, rather than tracking errors, are used to update the neural adaptation laws, which are independent of the tracking error dynamics, resulting in two time-scales to govern the entire system. The stability property of the closed-loop network is established via Lyapunov analysis, and transient property is quantified in terms of L2 norms of the derivatives of neural weights, which are shown to be smaller than the classical neural dynamic surface control approach. Comparative studies are given to show the substantial improvements of the proposed new method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

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李纪强 , 张国庆 , 黄晨峰 , 等 . 考虑执行器故障的无人帆船事件触发控制 [J ] . 系统工程与电子技术 , 2022 , 44 ( 1 ): 242 - 249 . DOI: 10.12305/j.issn.1001-506X.2022.01.30 http://doi.org/10.12305/j.issn.1001-506X.2022.01.30 针对实际海洋环境下, 无人帆船在艏向跟踪控制任务中存在的模型参数未知、控制输入频繁抖振和执行器磨损等问题, 提出一种考虑执行器故障的无人帆船事件触发控制算法。首先, 采用径向基函数神经网络(radius based function neural networks, RBF-NNs)对系统的未知模型参数进行在线逼近。其次, 在无人帆船艏向数学模型中引入执行器故障模型, 并且在艏向控制器设计中考虑帆结构造成的转船力矩, 设计基于事件触发机制的艏向控制律来减少控制输入的频繁抖振和执行器磨损。最后, 通过李雅普诺夫稳定性判据证明了所提控制算法满足半全局一致有界(semi-global uniform ultimate bounded, SGUUB)稳定。数值仿真结果表明, 相比于传统的艏向控制算法, 所提算法能够在保证艏向控制性能的基础上, 极大地降低控制输入的频繁抖振和减少执行器的磨损。

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