基于改进势场法的无人机编队协同避障控制算法

COOPERATIVE OBSTACLE AVOIDANCE CONTROL ALGORITHM FOR UAV FORMATION BASED ON IMPROVED POTENTIAL FIELD METHOD

为了解决多无人机存在的自碰撞与障碍碰撞及编队通信架构等问题,在二阶模型的编队系统基础上,提出一种由图论和人工势场理论相结合的分布式编队控制策略。依据运动学原理建立无人机模型,以固定无向的通信拓补结构为基础,引入分段思想、旋转力、机间势场力来改进势场合力函数,以解决可能出现的目标不可达、死锁、编队安全问题,精准实现编队避障、避碰与航迹预规划;根据一致性理论对无人机状态误差进行修正,设计编队协同避障控制律以实现期望状态一致与航迹规划;通过构造Hamilton函数与反证法进行稳定收敛性分析,证明所提出控制算法的收敛一致性。通过仿真结果表明,无人机编队能够有效进行避障并快速达到期望一致。

In order to solve the problems of self-collision,obstacle avoidance and formation communication architecture of UAVs,we propose a distributed formation control strategy which combines graph theory and artificial potential field theory based on the formation system with the second-order model.The UAV model was established according to the kinematics principle.On the basis of the fixed undirected communication extension structure,we introduced the segmentation idea,rotation force and inter aircraft potential field force to improve the potential field resultant force function,so as to solve the possible target unreachable,deadlock and formation safety,and accurately realize formation obstacle avoidance,collision avoidance and track planning.According to the consistency theory,the UAV state error was corrected,and the formation cooperative obstacle avoidance control law was designed to achieve the desired state consistency and track planning.By constructing Hamilton function and inverse proof method,we analyzed the stability convergence of the proposed algorithm and proved its convergence consistency.The simulation results show that the UAV formation can effectively avoid obstacles and quickly achieve the desired consistency.