系统工程与电子技术 ›› 2025, Vol. 47 ›› Issue (1): 230-243.doi: 10.12305/j.issn.1001-506X.2025.01.24

• 制导、导航与控制 • 上一篇    下一篇

基于运动约束的无人机编队一致性优化算法

刘金鑫, 盛蔚, 张玉民   

  1. 北京航空航天大学仪器科学与光电工程学院, 北京 100191
  • 收稿日期:2024-01-24 出版日期:2025-01-21 发布日期:2025-01-25
  • 通讯作者: 盛蔚
  • 作者简介:刘金鑫(2000—), 男, 硕士研究生, 主要研究方向为无人机编队控制
    盛蔚(1971—), 女, 教授, 博士, 主要研究方向为微小型全自主无人机飞行控制系统、微小型惯性基多源组合导航系统、分布式航空遥感位置姿态测量系统、微纳惯性器件机理与设计
    张玉民(1971—), 男, 副教授, 博士, 主要研究方向为飞行器导航与控制、故障诊断与容错控制

Optimization algorithm for UAV formation consensus based on motion constraint

Jinxin LIU, Wei SHENG, Yumin ZHANG   

  1. School of Instrument Science and Optoelectronic Engineering, Beihang University, Beijing 100191, China
  • Received:2024-01-24 Online:2025-01-21 Published:2025-01-25
  • Contact: Wei SHENG

摘要:

针对无人机运动约束下的编队任务研究标准二阶一致性控制算法的优化问题。首先, 结合编队信息, 基于虚拟结构法思想, 设计含虚拟参考点的二阶一致性编队控制算法, 使得编队收敛于指定队形, 解决标准二阶一致性控制算法的收敛状态与各无人机初值有关以及收敛位置趋于一致的问题, 得到编队渐近收敛的条件。其次, 引入饱和函数得到运动约束条件下的渐近收敛的二阶一致性编队控制算法, 设计无人机编队高度、航向、速度通道控制器。最后, 设计无人机编队队形集结仿真实验, 对比相同饱和函数不同一致性方法的编队控制算法、相同一致性方法不同饱和函数的编队控制算法, 验证了优化算法的有效性和快速性。

关键词: 无人机编队, 一致性编队控制算法, 虚拟参考点, 运动约束, 饱和函数

Abstract:

For formation tasks under unmanned aerial vehicle (UAV) motion constraints, optimization problem of standard second-order consensus control algorithm is studied. First of all, based on the formation information, the second-order consensus formation control algorithm with virtual reference point is designed, which makes the formation converge to the specified formation. The problem that the convergence state of the standard second-order consensus control algorithm is related to the initial value of each UAV and the convergence position tends to agree is solved. And the condition of asymptotic convergence of formation is obtained. Secondly, the saturation function is introduced to design the asymptotically converged second-order consensus formation control algorithm under the motion constraint, and then designed the UAV formation altitude, heading and velocity channel controller. Finally, simulation experiment of UAV formation assembly is designed to compare the formation control algorithm with different consensus methods of the same saturation function and the formation control algorithm with different saturation function of the same consensus method, and verify the effectiveness and speed of the optimization algorithm.

Key words: unmanned aerial vehicle (UAV) formation, consensus formation control algorithm, virtual reference point, motion constraint, saturation function

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