【摘要】 针对输入故障下的固定翼无人机“多领导者-多跟随者”集群的鲁棒高精度仿射编队机动问题，基于自抗扰控制、固定时间控制和预设性能控制，提出了一种协调与飞行解耦的多层控制方案。针对集群仿射编队机动的上层协调，设计了一种新型分布式固定时间状态估计器，适应于局部单向交互下参考轨迹的快速生成；针对集群编队的底层飞行，基于自抗扰控制框架设计了底层鲁棒控制器，采用固定时间扩张状态观测器快速估计由外部干扰和输入故障引起的总匹配干扰，并设计了一种自适应神经网络用于拟合动力学耦合与模型不确定性引入的系统非匹配干扰，面向飞行中的控制精度约束，提出了一种新型固定时间预设性能函数，结合动态面技术并引入辅助系统，设计了一种抗饱和的预设性能反演控制器，最终实现各无人机高精度机动飞行。通过数值仿真验证了在输入故障下无人机集群编队机动的有效性和鲁棒性。更多还原

【Abstract】 A multi-layer control scheme decoupling coordination and flight is proposed based on Active Disturbance Rejection Control(ADRC), fixed-time control and prescribed performance control(PPC)for robust high-precision affine formation maneuver of fixed-wing UAV "multi-leader-multi-follower" swarm under the input faults and saturation. Firstly, a novel distributed fixed-time state estimator(DFTSE)is designed for the upper-layer coordination of the swarm affine formation maneuver, which is adapted to the fast generation of the reference trajectory under the local unidirectional interaction. After that, a bottom-layer robust flight controller is designed based on the ADRC framework to realize the high-precision maneuvering flight of each UAV. A fixed-time extended state observer is employed to quickly estimate the total matching disturbance caused by external disturbances and input faults, and an adaptive neural network(NN)is designed for fitting the non-matching disturbance of system introduced by dynamics coupling and model uncertainty. In addition, a new fixed-time prescribed performance function is proposed for the control of accuracy constraints during flight, and an anti-saturation prescribed performance backstepping controller is designed by combining the dynamic surface technique into an auxiliary system. The Lyapunov stability theory is applied to prove the stability of the closed-loop system under satisfying the performance constraints. Finally,the effectiveness and robustness of UAV swarm formation maneuver under input faults and saturation are verified by numerical simulations.更多还原