改进Quatre算法的无人机编队快速集结方法

doi:10.12305/j.issn.1001-506X.2022.09.18

摘要/Abstract

摘要：

为了提高多无人机在编队集结过程中的稳定性, 提出基于改进拟仿射类进化(improved quasi-affine transformation evolutionary, IQuatre)算法的无人机编队集结方法。首先, 基于分布式模型预测控制(distributed model predictive control, DMPC)建立无人机编队的运动预测模型, 通过预测无人机的“未来态”规避编队内碰撞风险, 滚动优化的数学模型提高了无人机到达指定位置的稳定性, 使得无人机更好、更快地加入编队飞行; 其次, 对Quatre算法进行种群优化改进, 将携带最优基因的父代个体有选择性地加入子代种群, 加快种群收敛。实验结果表明, 基于DMPC的无人机编队集结未出现碰撞情况, 减小了无人机调整状态过程中出现的位置偏差; 对比仿真验证了IQuatre算法能够提高编队集结的稳定性, 较原Quatre算法减少了5.2%的平均迭代次数, 在计算时间上节约了4.6%, 位置误差减小了0.45 m。

关键词: 无人机编队, 分布式模型预测控制, 改进拟仿射类进化算法, 滚动优化, 种群优化

Abstract:

To improve the stability of multiple unmanned aerial vehicle (UAV) in the process of formation assembly, this paper proposes a UAV formation method based on improved quasi-affine transformation evolutionary (IQuatre) algorithm. First of all, based on distributed model predictive control (DMPC), a motion prediction model of the UAV formation is established. By predicting the "future state" of the UAV, the risk of collision within the formation is avoided. The mathematical model of rolling optimization improves the stability of the UAV to reach the designated position. UAV is better and faster to join the formation flight. Secondly, the Quatre algorithm is improved on population optimization by the parent individuals carrying the best genes selectively added to the offspring population to speed up population convergence. The experimental results show that the UAV formation based on the DMPC has no UAV collision, and reduces the position deviation during the UAV adjustment state. Comparing simulations verify that the IQuatre algorithm can improve the stability of the formation assembly. Compared with the original Quatre algorithm, the average number of iterations is reduced by 5.2%, the calculation time is saved by 4.6%, and the position error is reduced by 0.45 m.

Key words: unmanned aerial vehicle (UAV) formation, distributed model predictive control (DMPC), improved quasi-affine transformation evolutionary (IQuatre), rolling optimization, population optimization

中图分类号:

TP301

孙田野, 孙伟, 吴建军. 改进Quatre算法的无人机编队快速集结方法[J]. 系统工程与电子技术, 2022, 44(9): 2840-2848.

Tianye SUN, Wei SUN, Jianjun WU. UAV formation rapid assembly method based on improved Quatre algorithm[J]. Systems Engineering and Electronics, 2022, 44(9): 2840-2848.

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参数	速度/(m/s)	航向角/(°)	俯仰角/(°)	加速度/(m/s²)	航向角速度/(°)	俯仰角速度/(°)
最小参数	30	-180	45	-0.7	-15	-15
最大参数	50	180	135	0.7	15	15

算法	参数设置
Pro-DE	变异概率0.4, 交叉概率0.6
DE	变异概率0.6, 交叉概率0.6
GA	交叉概率0.3, 变异概率0.1
PSO	权重1, 学习系数0.5
Quatre	步长0.7
IQuatre	步长0.7

算法	5架无人机	15架无人机	25架无人机
IQuatre	20	57	89
Quatre	21	59	94
Pro-DE	28	80	127
DE	39	115	186
GA	37	108	181
PSO	78	232	389

算法	IQuatre	Quatre	Pro-DE	DE	GA	PSO
距离	1.62	2.07	2.93	3.78	19.8	1.95

算法	IQuatre	Quatre	Pro-DE	DE	GA	PSO
距离	1.7	2.02	3.12	11.03	24.14	2.99