无人机领导的多无人艇系统固定时间优化编队控制
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南京理工大学 自动化学院,南京 210094

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E-mail: xiangzr@mail.njust.edu.cn.

中图分类号:

TP273

基金项目:

国家自然科学基金项目(62373191,62303224);海装十四五预研课题项目(3020903010202).


Fixed-time optimal formation control for multi-unmanned surface vessels under the leadership of unmanned aerial vehicle
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School of Automation,Nanjing University of Science and Technology,Nanjing 210094,China

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    摘要:

    针对多无人艇(unmanned surface vessels,USVs)编队系统中USV视野受限等问题,提出一种以无人机(unmanned aerial vehicles,UAV)作为多USV编队领导者的模型.针对UAV领导的多USV系统水空协同编队问题,设计一种固定时间的优化编队控制算法.在对USV、UAV进行三自由度动力学建模的基础上构建增广系统,并建立一个以优化控制输入及编队误差为目标的性能指标函数.所提出的辨识器-执行者-评价者结构的强化学习算法中,辨识器可以精确辨识系统中的未知非线性动态,通过评价者完成对最优性能指标函数值的评估、执行者更新控制策略两个步骤不断优化控制策略以逼近最优,进而利用Lyapunov方法证明UAV-USV系统编队误差能在固定时间内收敛.最后,通过仿真模拟验证了所提出算法的有效性.

    Abstract:

    Due to the limited visibility of unmanned surface vessel(USVs) in multi-USV formation systems, this paper proposes a model with an unmanned aerial vehicle(UAV) as the leader of the USV formations. A fixed-time optimal formation control algorithm is designed for the formation of multi-USVs under UAV leadership. Building upon the three-degree-of-freedom dynamic modeling of USVs and UAVs, an augmented system is constructed. A performance index function that considers input cost and formation error is established. In the proposed reinforcement learning algorithm with an identifier-actor-critic structure, unknown nonlinear system dynamic is approximated by the identifier. The actor and critic for executing control behavior and evaluating control performance tunes simultaneously towards the optimal solution. Furthermore, it is proven that the formation error of the UAV-USV system can converge to a small region around zero within a fixed time. The effectiveness of the proposed algorithm is verified by simulation examples.

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向雨竹,邹文成,郭健,等.无人机领导的多无人艇系统固定时间优化编队控制[J].控制与决策,2025,40(1):223-230

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  • 在线发布日期: 2024-12-12
  • 出版日期: 2025-01-20
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