基于预设性能的无人机主动抗干扰编队控制
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V24;TP273

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国家自然科学基金项目(U25A20453, 62573230);江苏省自然科学基金优秀青年基金项目(BK20230091).


Active disturbance rejection formation control of UAVs based on prescribed performance
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    摘要:

    无人机编队飞行过程会受到外界阵风、内部参数摄动、未建模动态等多源干扰以及执行器故障的影响, 此外, 在队形动态调整阶段, 编队误差大幅变化可能会导致碰撞等安全问题. 鉴于此, 针对无人机编队系统受到的多源干扰、执行器故障影响以及编队误差收敛过程中的动态约束问题, 提出一种基于预设性能和广义比例积分观测器的无人机主动抗干扰编队控制方法. 通过引入基于双曲余切函数的新型预设性能算法, 在无需编队系统初始状态信息的情况下, 能够保证编队误差在预设的包络线内收敛, 满足编队误差的动态约束. 通过广义比例积分观测器的引入, 能够实现编队系统中高阶时变干扰的估计与补偿, 拓宽干扰处理种类, 提升编队系统控制精度.

    Abstract:

    The unmanned aerial vehicle (UAV) formation flying process will be affected by external gusts, internal parameter perturbations, unmodeled dynamics and other multi-source disturbances. In addition, during the formation dynamic adjustment stage, the large change of formation error may lead to safety problems such as collision. This paper proposes an active disturbance rejection formation control of UAVs based on prescribed performance to attenuate the multi-source disturbances’ influence and guarantees the satisfaction of formation error. By introducing a novel prescribed performance algorithm based on the hyperbolic tangent function, the proposed method ensures that the formation error converges within the preset envelope and meets the dynamic constraint of formation error without requiring initial state information of the formation system. Through the introduction of a generalized proportional integral observer (GPIO), the estimation and compensation of high-order time-varying disturbances in a formation system are realized, the types of disturbances which can be handled are broadened, and the control accuracy of the formation system is improved.

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赵振华,陈谷雨,姜斌,等.基于预设性能的无人机主动抗干扰编队控制[J].控制与决策,2026,41(6):1553-1562

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  • 收稿日期:2025-11-18
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  • 在线发布日期: 2026-05-13
  • 出版日期: 2026-06-10
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