基于CVPF算法的无人机编队系统设计

Research on UAV formation system based on CVPF algorithm

摘要:

随着互联网和通信技术的不断发展,无人机被广泛应用于各个领域。但现有的无人机编队控制方法,稳定性较差,无法保持良好的位置和速度一致性。因此研究提出了基于一致性联合虚拟势场的无人机编队控制方法,该方法将人工势场法与一致性控制原理融合,对目标不可达进行优化,引入惯性偏移量解决无人机惯性问题,并设计了无人机编队控制系统。实验结果表明,无人机在x和y轴方向的位置一致性测试性能良好,无人机3在30s时y轴方向位移出现波动,最大差值10m。无人机编队的实际悬停位置与期望悬停位置误差为0.16m,无人机3在x和y轴方向都出现的速度波动,与其他无人机速度方向相反,最大差值分别为6.2m/s和5.8m/s,CVPF算法的编队变换速度分别比其他算法快了1.6s、1.2s、1.8s以及2.0s,计算复杂性仅比长机-僚机法高出6ms。由此可得,研究提出的算法能够有效控制无人机编队的位置和速度一致性,防止出现安全事故,解决了惯性和目标不可达问题。

Abstract:

With the continuous development of the Internet and communication technology, unmanned aerial vehicles (UAVs) are widely used in various fields. However, the existing UAV formation control methods have poor stability and cannot maintain good position and velocity consistency. Therefore, the study proposes a UAV formation control method based on coherent joint virtual potential field, which integrates the artificial potential field method with the coherent control principle, optimizes the target unreachability, introduces inertial offset to solve the inertia problem of UAV, and designs the UAV formation control system. The experimental results show that the UAVs perform well in the position consistency test in the x and y-axis directions, and UAV 3 shows fluctuations in the displacement in the y-axis direction at 30 s, with a maximum difference of 10 m. The error between the actual hovering position and the desired hovering position of the UAV formation is 0.16 m, and the velocity fluctuations of UAV 3 in both the x and y-axis directions are in the opposite direction of the velocity of the other UAVs, with a maximum difference of 6.2 m /s and 5.8m/s, the formation transformation speed of CVPF algorithm is faster than other algorithms by 1.6s, 1.2s, 1.8s, and 2.0s respectively, and the computational complexity is only 6ms higher than that of the long aircraft-wingman method.It can be concluded that the algorithm proposed in the study can effectively control the position and velocity consistency of UAV formation, prevent safety accidents, and solve the inertia and target unreachability problems.