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基于高阶人工势场的多智能体低震荡避障蜂拥控制
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V279

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陕西省科协青年人才托举计划项目(20240105);陕西省自然科学基础研究计划青年项目(2023-JC-QN-0728)


A Method of Controlling Multi-Agent System Low-Oscillation Collision-Free Flocking Based on High-Order Artificial Potential Field
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    摘要:

    针对蜂拥控制二阶系统存在震荡且初始响应慢的问题,通过整合多智能体系统所需人工势场通用性质,提出了高阶人工势场的蜂拥控制算法。将势场梯度视为智能体预期位置的偏差,从轨迹跟踪的角度出发设计控制率,并将人工势场海森矩阵引入到蜂拥控制之中,设计了一种基于能量的Lyapunov函数,分别证明了蜂拥控制方法的稳定性和多智能体系统运行过程的避障性。最后通过数值仿真计算,证明所提的高阶势场法显著提升了多智能体蜂拥控制的响应速度,有效缓和了多智能体系统的震荡现象。

    Abstract:

    Multi-agent system flocking control has been a research hot topic in recent years.In view of the problems that there remain oscillation and slow initial response in second-order flocking control systems, this paper proposes a flocking control algorithm incorporated higher-order artificial potential fields by integrating the general properties of artificial potential fields required for multi-agent systems.Viewing the potential field gradient as the deviation of the agent's expected position, the control law is designed from the perspective of trajectory tracking. And, the Hessian matrix of the artificial potential field is introduced into the flocking control, and an energy-based Lyapunov function is designed to prove out the stability of the flocking control method and the obstacle avoidance during the operation of the multi-agent system separately.Thenumerical simulation results show that the proposed high-order potential field method achieves a significant increase in the response speed of multi-agent flocking control, effectively suppressing the system oscillations.

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万路军,李 强,肖博漪,田继伟,钟 赟.基于高阶人工势场的多智能体低震荡避障蜂拥控制[J].空军工程大学学报,2026,27(2):54-61

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  • 在线发布日期: 2026-04-27
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