Containment control of networked autonomous underwater vehicles with model uncertainty and ocean disturbances guided by multiple leaders
Containment control of networked autonomous underwater vehicles with model uncertainty and ocean disturbances guided by multiple leaders
复制标题
具有模型不确定性和多领导者引导的海洋扰动的网络化自主水下航行器的遏制控制
DOI：
10.1016/j.ins.2015.04.025
复制
发表时间：
2015-09-20
影响因子：
8.1
通讯作者：
Wang, Wei
中科院分区：
文献类型：
--
作者：
Peng, Zhouhua;Wang, Dan;Wang, Wei
研究了多个动态领导者在有向网络上引导的网络化自主水下航行器的包容控制问题。每一个潜水器都受到模型不确定性和未知的时变海洋扰动的影响。提出了一种新的基于预测器的神经动态面控制设计方法，设计了自适应包容控制器，使飞行器的轨迹收敛到由先导飞行器的轨迹所张成的凸船体上.具体而言，迭代神经更新法律，预测误差的基础上，构造，使每个车辆的未知动态的准确识别，不仅在稳态，而且在瞬态。此外，这个结果被扩展到输出反馈的情况下，只有位置偏航信息可以测量。设计了一种神经网络观测器来恢复未测速度信息。基于观测到的相邻航行器的速度，设计了分布式输出反馈包容控制器，在该控制器下，可以实现包容，而不受模型不确定性，未知的海洋扰动，和未测量的速度信息。对于这两种情况，Lyapunov-Krasovskii泛函被用来证明闭环误差信号的一致最终有界性。比较研究表明，所提出的方法的性能改进。(C)2015 Elsevier Inc. All rights reserved.
This paper considers the containment control of networked autonomous underwater vehicles guided by multiple dynamic leaders over a directed network. Each vehicle is subject to model uncertainty and unknown time-varying ocean disturbances. A new predictor-based neural dynamic surface control design approach is presented to develop the adaptive containment controllers, under which the trajectories of vehicles converge to the convex hull spanned by those of the leaders. Specifically, iterative neural updating laws, based on prediction errors, are constructed, which enable the accurate identification of the unknown dynamics for each vehicle, not only in steady state but also in transient state. Furthermore, this result is extended to the output-feedback case where only the position-yaw information can be measured. A neural observer is developed to recover the unmeasured velocity information. Based on the observed velocities of neighboring vehicles, distributed output-feedback containment controllers are devised, under which the containment can be achieved regardless of model uncertainty, unknown ocean disturbances, and unmeasured velocity information. For both cases, Lyapunov-Krasovskii functionals are used to prove the uniform ultimate boundedness of the closed-loop error signals. Comparative studies are given to show the performance improvement of the proposed methods. (C) 2015 Elsevier Inc. All rights reserved.