Controlling a distributed autonomous unmanned aerial vehicle (UAV) formation is usually considered in the context of recovering the connectivity graph should a single UAV agent be lost. At the same time, little focus is made on how such loss affects the dynamics of the formation as a system. To compensate for the negative effects, we propose an adaptation algorithm that reduces the increasing interaction between the UAV agents that remain in the formation. This algorithm enables the autonomous system to adjust to the new equilibrium state. The algorithm has been tested by computer simulation on full nonlinear UAV models. Simulation results prove the negative effect (the increased final cruising speed of the formation) to be completely eliminated.
翻译:控制分布式自动无人驾驶飞行器(无人驾驶飞行器)编组通常在一旦失去单一无人驾驶飞行器制剂时,在恢复连接图的背景下加以考虑;同时,很少关注这种损失如何影响编组的系统动态;为弥补负面影响,我们建议采用适应算法,减少编组中仍留在编组中的无人驾驶飞行器制剂之间日益增加的相互作用;这种算法使自动系统能够适应新的平衡状态;这种算法已经通过计算机模拟非线性无人驾驶飞行器全模型测试了算法;模拟结果证明将完全消除负面效应(编组最后游动速度加快)。