摘要
针对一致性算法结合人工势场法在复杂受限环境中易触发扰动放大与通信拓扑失稳,从而诱发无人机位置、速度以及拓扑的无序演化并削弱集群通行性能的问题,提出一种基于熵驱动的集群通行控制策略,通过实时感知位置熵、速度熵和拓扑熵并自适应调整控制输入与邻接结构,增强系统的协同自组织能力。仿真结果表明,所提方法能够显著抑制集群无序性,较一致性控制策略,综合熵指标下降超过60%,同时在受限通行阶段,平均最小障碍间距提升25%,且在扰动后末段速度衰减幅度降低59%,从而定量验证了所提策略在通行安全性与稳定性方面的优势。
To address the performance degradation of consensusAPF control in complex constrained environments due to disturbance amplification and communication-topology instability,which induces disorder in UAV positions,velocities,and network topology,an entropy-driven swarm passage control strategy is proposed which continuously evaluates position,velocity,and topological entropy and adaptively adjusts control inputs and neighborhood structures to strengthen the system's self-organizing capability.Simulation results demonstrate that the proposed method significantly suppresses disorder within the swarm,achieving over a 60%reduction in overall entropy.During constrained traversal,the average minimum obstacle clearance increases by 25%,and the late-stage speed decay after disturbances is reduced by 59%,thereby quantitatively demonstrating the superiority of the proposed strategy in traversal safety and stability.
作者
叶正言
刘云平
乔馨霆
谢双双
董娟
徐梁
YE Zhengyan;LIU Yunping;QIAO Xinting;XIE Shuangshuang;DONG Juan;XU Liang(Nanjing University of Information Science and Technology,Nanjing 210044,China;Pla Naval Submarine Academy,Dalian 116018,China)
出处
《中国惯性技术学报》
北大核心
2026年第2期202-212,共11页
Journal of Chinese Inertial Technology
基金
国家自然科学基金(51875293)
空间智能控制技术重点实验室稳定支持基金(HTKJ2023KL502020)。
关键词
无人机
集群运动
熵驱动
群体熵度量
unmanned aerial vehicles
cluster motion
entropy-driven
group entropy metric
