无人机集群吊挂的预设性能抗干扰协同控制-自主智能无人系统专刊

  • 陈欣宇 ,
  • 李海旭 ,
  • 张霄宁 ,
  • 刘鹏 ,
  • 范云生
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  • 1. 大连海事大学
    2. 中国船舶集团系统工程研究院

收稿日期: 2025-12-03

  修回日期: 2026-04-08

  网络出版日期: 2026-04-09

基金资助

国家基础科研重点项目;国家重点研发计划项目;国家自然科学基金项目;辽宁省中试基地中试验证类科技项目;大连市揭榜挂帅技术攻关项目;中央高校基本科研业务费专项基金资金

Prescribed Performance and Anti-Disturbance Formation Control for Multi-UAV Cooperative Slung-Load System

  • CHEN Xin-Yu ,
  • LI Hai-Xu ,
  • ZHANG Xiao-Ning ,
  • LIU Peng ,
  • FAN Yun-Sheng
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Received date: 2025-12-03

  Revised date: 2026-04-08

  Online published: 2026-04-09

摘要

针对无人机集群吊挂系统在执行器故障、输入饱和及负载质量变化等内部状态约束,以及风场扰动和下洗气流等外部扰动作用下的多机协同稳定控制问题,提出了一种基于改进预设性能控制(Improved Prescribed Performance Control, IPPC)、积分反步滑模控制与扩展干扰观测器(Extended Disturbance Observer, EDO)相结合的集群吊挂抗干扰协同控制方法。首先,利用Udwadia-Kalaba方程建立了无人机集群吊挂系统的约束动力学模型,实现了无人机集群协同与吊挂负载之间的解耦。其次,基于图论方法将吊挂负载等效为虚拟领航者,设计无人机集群的期望轨迹,以实现系统在空间上的一致性与协同性。同时引入改进预设性能控制策略,将系统误差动态约束在预定范围内,从而有效防止无人机间的碰撞并保持协同控制的稳定性。进一步地,设计了积分反步滑模控制器,结合EDO对模型不确定性和外部扰动进行在线估计与补偿,提高了系统的鲁棒性与抗干扰能力。最后,通过李雅普诺夫稳定性分析严格证明了所提控制策略的全局稳定性,并通过仿真实验验证了该方法在执行器故障、输入饱和及风场干扰条件下的优越跟踪性能与协同控制效果。

本文引用格式

陈欣宇 , 李海旭 , 张霄宁 , 刘鹏 , 范云生 . 无人机集群吊挂的预设性能抗干扰协同控制-自主智能无人系统专刊[J]. 航空学报, 0 : 1 -0 . DOI: 10.7527/S1000-6893.2026.33184

Abstract

In this paper, a cooperative control strategy that integrates Improved Prescribed Performance Control (IPPC), Integral Backstepping Sliding Mode Control (IBSMC), and an Extended Disturbance Observer (EDO) is proposed to address the stable control problem of a multi-UAV cooperative slung-load system subject to internal state constraints, such as actuator faults, input saturation, and varying payload mass, as well as external disturbances including wind field effects and downwash airflow. First, the Udwadia–Kalaba equation is employed to establish the constrained dynamic model of the multi-UAV cooperative slung-load system, accurately capturing the coupling relationship between the quadrotors and the slung-load. Then, based on graph theory, the slung-load is regarded as a virtual leader, and the desired trajectories of each quadrotor are generated to ensure spatial consistency and coordination of the system. Meanwhile, an improved prescribed performance control strategy is introduced to dynamically constrain the system error within predefined bounds, effectively preventing inter-quadrotor collisions and maintaining formation stability. Furthermore, an integral backstepping sliding mode controller is designed and combined with the EDO to achieve online estimation and compensation of model uncertainties and external disturbances, thereby enhancing the system’s robustness and disturbance rejection capability. Finally, Lyapunov-based stability analysis rigorously proves the global stability of the proposed control strategy, and simulation results demonstrate its superior tracking accuracy and cooperative performance under actuator faults, input saturation, and wind field disturbances.

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