联合变论域模糊PID的四旋翼无人机编队控制方法

Joint Variable Domain Fuzzy PID Control Method for Four rotor UAV Formation Control

摘要:

面向复杂低空物流运输场景中四旋翼无人机编队系统存在的高动态非线性耦合、异构扰动源导致的姿态协同失准与构型保持困难等问题,提出一种耦合僚机姿态的联合变论域模糊PID编队控制方法。针对全局坐标系输入在转向过程中,因未融合局部航向信息而引发的相对方位误判与控制滞后,引入基于僚机航向角的姿态关联输入模型,实现相对位置与速度的精准实时解算。设计多机协同论域自适应调整机制,通过协同伸缩因子动态扩展/收缩输入输出论域,显著增强系统对非线性动态扰动与多机耦合效应的适应能力。在此基础上,构建基于比例?积分?微分独立修正的PID参数协同整定策略,结合控制周期实时调节微分作用强度,有效抑制积分饱和与噪声放大,提升编队整体协同鲁棒性与单机动态纠偏性能。在32架无人机参与的城市物流配送实测中,所提方法在密集障碍、突发风扰及通信遮挡等复杂条件下,仍维持编队构型稳定,姿态一致性误差个体差异小于0.5°,三维空间位置协同集中且轨迹平滑,验证了该方法在强动态环境下具有优异的构型保持能力与高精度协同控制性能。

Abstract:

A joint variable domain fuzzy PID formation control method with coupled wingman attitude is proposed to address the issues of high dynamic nonlinear coupling, attitude coordination misalignment caused by heterogeneous disturbance sources, and difficulty in maintaining configuration in complex low altitude logistics transportation scenarios of quadcopter unmanned aerial vehicle formation systems. In response to the relative orientation misjudgment and control lag caused by the lack of fusion of local heading information during the turning process of the global coordinate system input, an attitude correlation input model based on the wingman heading angle is introduced to achieve accurate real-time calculation of relative position and velocity. Design a multi machine collaborative domain adaptive adjustment mechanism that dynamically expands/contracts the input-output domain through collaborative scaling factors, significantly enhancing the system"s adaptability to nonlinear dynamic disturbances and multi machine coupling effects. On this basis, a PID parameter collaborative tuning strategy based on proportional integral derivative independent correction is constructed, and the differential action strength is adjusted in real time by combining the control cycle, effectively suppressing integral saturation and noise amplification, and improving the overall collaborative robustness of the formation and the dynamic correction performance of the single machine. In the actual testing of urban logistics distribution involving 32 drones, the proposed method maintained stable formation configuration under complex conditions such as dense obstacles, sudden wind disturbances, and communication obstructions, with individual differences in attitude consistency error less than 0.5 °. The three-dimensional spatial position was coordinated and concentrated, and the trajectory was smooth. This verified that the method has excellent configuration maintenance ability and high-precision collaborative control performance in strong dynamic environments.