在四旋翼无人机编队跟踪问题中，由于四旋翼无人机未建模动态以及外部干扰的存在，如何实现无人机的编队跟踪以及安全防碰撞是极大的挑战。针对这些挑战，提出了一种基于参数自适应方法、分布式扩张状态观测器和倒数控制障碍函数的四旋翼无人机方位编队控制方案。首先，为领导者-跟随者框架无人机集群设计了一种融合参数自适应方法和分布式扩张状态观测器的状态-扰动估计框架，基于无人机之间方位角、方位角变化率以及相对距离信息，在线估计跟随者全局位置、速度以及受到的内外干扰。继而，基于估计状态和期望轨迹，设计了跟踪期望位置、速度的控制Lyapunov函数（CLF）。针对四旋翼无人机编队中无人机之间的防碰撞需求，设计了同时考虑相对位置和相对速度的倒数控制障碍函数（RCBF），以实现动态防碰撞。在此基础上，设计了利用二次规划求解的编队防碰撞安全控制器，实时求解最优控制量，并分析了控制器规划问题的可解性。仿真表明，在未建模动态与外部干扰的影响下，所提方案能有效完成编队形成、保持任务；状态-扰动估计框架能精准估计全局状态与干扰；对比实验进一步验证了防碰撞策略的
有效性以及整体控制方案的优势。
In quadrotor formation tracking, the presence of unmodeled dynamics and external disturbances makes it highly challenging to simultaneously achieve accurate formation tracking and safe collision avoidance. To address these issues, a bearing-based formation control scheme for quadrotor swarms is proposed, integrating a parameter-adaptation method, a distributed extended state observer (DESO), and a reciprocal control barrier function (RCBF).First, within a leader–follower framework, a state–disturbance estimation architecture is developed by combining parameter adaptation with a distributed extended state observer. Based on the inter-UAV bearing angles, bearing-rate information, and relative distances, the proposed framework online estimates each follower’s global position and velocity, as well as the lumped internal and external disturbances.Subsequently, a control Lyapunov function (CLF) is constructed based on the estimated states and desired trajectories to ensure tracking of the desired positions and velocities. To address the inter-agent collision-avoidance requirement in quadrotor formations, a reciprocal control barrier function (RCBF) is designed that simultaneously considers relative positions and relative velocities, thereby achieving dynamic collision avoidance.On this basis, a formation-safe controller is formulated as a quadratic programming (QP) problem, where the optimal control input is computed in real time. The feasibility of the resulting QP is also analyzed. Simulation results demonstrate that, despite the influence of unmodeled dynamics and external disturbances, the proposed scheme can effectively accomplish formation establishment and maintenance tasks. The state–disturbance estimation framework provides accurate global
state and disturbance estimates. Comparative studies further verify the effectiveness of the collision-avoidance strategy and highlight
the overall advantages of the proposed control scheme.
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