弱通信下无人潜航器事件触发一致性协同控制  

Event-triggered consensus cooperative control of unmanned underwatervehicle under adverse communication condition

作　　者：赵万兵 夏元清[1] 戴荔[1] 张元 ZHAO Wanbing;XIA Yuanqing;DAI Li;ZHANG Yuan(School of Automation,Beijing Institute of Technology,Beijing 100081,China)

机构地区：[1]北京理工大学自动化学院,北京100081

出　　处：《系统工程与电子技术》2025年第2期591-599,共9页Systems Engineering and Electronics

基　　金：国家自然科学基金(62303050);中国博士后科学基金(2023M730254,2024T171122);国家资助博士后研究人员计划(GZB20230936)资助课题。

摘　　要：针对水下无人潜航器(unmanned underwater vehicle, UUV)集群在弱通信条件下的一致性协同控制问题,考虑水下群间通信存在的高延时、低带宽、需具有隐蔽性等弱通信特点,设计基于强化学习的事件触发智能一致性协同控制架构,以实现UUV集群在弱通信条件下的有效协同。首先,设计一个事件触发分布式观测器,该观测器利用领导者与邻居的动态交互信息,来估计弱通信条件下UUV所需的跟踪参考信号。随后,采用强化学习方法直接从系统交互中学习最优控制策略。最后,通过仿真结果验证了所提方法的有效性。Aiming at the problem of consensus collaborative control of unmanned underwater vehicle(UUV)clusters under adverse communication conditions,considering the adverse communication characteristics of high latency,low bandwidth,and the need for stealth in underwater inter-cluster communication,a reinforcement learning based event-triggered intelligent consensus collaborative control architecture is designed to achieve effective collaboration of UUV clusters under adverse communication conditions.Firstly,an event-triggered distributed observer is devised which utilizes dynamic interaction information between leaders and neighbors to estimate the tracking reference signal required for UUVs under adverse communication conditions.Subsequently,reinforcement learning methods are used to directly learn the optimal control strategy from system interactions.Finally,the effectiveness of the proposed method is validated through simulation results.

关 键 词：弱通信 事件触发 一致性协同控制 强化学习 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]