基于预设时间一致性理论的无人机编队控制

doi:10.12382/bgxb.2024.0863

摘要/Abstract

摘要：

无人机编队可以实现复杂的集体任务,降低单个无人机的风险和操作难度。针对三维场景下的无人机集群编队控制问题,基于预设时间稳定理论和多智能体一致性理论,设计领-从结构下的分布式编队复合控制方法。通过分析无人机实际输入与等效控制之间的关系,建立多机运动学模型。为提高无人机对外部扰动的鲁棒性,结合自抗扰控制理论设计一种预设时间收敛扩张状态观测器,实现对扰动的在线估计。进一步,考虑到只有与领航者连通的跟随者能获取领航者的状态信息,提出一种预设时间收敛的分布式估计器,以快速估计领航者的状态。结合观测器及估计器的输出,提出一种预设时间收敛的一致性编队控制协议,并通过Lyapunov理论证明闭环系统的预设时间稳定性。通过构建数值仿真实验,验证了新方法的有效性。研究结果表明,新设计的控制方法在存在外部扰动的情况下可以实现预设时间内稳定的无人机编队协同控制。

关键词: 无人机, 编队控制, 预设时间稳定, 扩张状态观测器, 分布式估计器, 多智能体一致性理论

Abstract:

Unmanned aerial vehicle (UAV) formation can execute complex collective tasks and reduce the risk and operation difficulty of a single UAV. A distributed formation compound control method with the leader-follower structure is designed based on the prescribed-time stability theory and multi-agent consensus theory for the control of UAV swarm formation in three-dimensional scene.Firstly,a multi-UAVs kinematic model is established by analyzing the relationship between the actual input and the equivalent control.In order to enhance the robustness of UAVs against external disturbances,a prescribed-time convergent extended state observer is designed to achieve online estimation of disturbance based on active disturbance rejection control theory.Furthermore,considering that only the followers connecting to the leader can access the leader's state information,a prescribed-time convergent distributed estimator is introduced to rapidly estimate the leader's state.On this basis,a prescribed-time convergent consensus formation control algorithm is proposed combined with the outputs of the observer and the estimator,and the prescribed-time stability of closed-loop system is proved by Lyapunov theory.The simulated results validate the effectiveness of the proposed method.The research results show that the proposed control method can achieve the stable cooperative control of UAV formation within a preset time in the presence of external disturbances.

Key words: unmanned aerial vehicle, formation control, prescribed-time stability, extended state observer, distributed estimator, multi-agent consensus theory

中图分类号:

TJ301

李俊辉, 王伟, 王雨辰, 纪毅. 基于预设时间一致性理论的无人机编队控制[J]. 兵工学报, 2025, 46(8): 240863-.

LI Junhui, WANG Wei, WANG Yuchen, JI Yi. Unmanned Aerial Vehicle Formation Control Based on Prescribed-time Consensus Theory[J]. Acta Armamentarii, 2025, 46(8): 240863-.

图/表 8

参考文献 28

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参数	无人机1	无人机2	无人机3	无人机4
位置跟踪误差/m	0.0001	0.0027	0.0058	0.0092
速度跟踪误差/(m·s^-1)	0.0011	0.0027	0.0734	0.0966
位置估计误差/m	3.1×10^-16	1.5×10^-14	1.3×10^-5	2.2×10^-5
速度估计误差/(m·s^-1)	1.9×10^-13	6.2×10^-7	3.1×10^-5	5.0×10^-5
加速度估计误差/(m·s^-2)	0	0	0	0
T_u扰动估计误差	0.3529	0.1912	0.0367	0.2274
5T_u扰动估计误差	0.0170	0.0087	0.0182	0.0638

参数	无人机1	无人机2	无人机3	无人机4
位置跟踪误差/m	0.0001	0.0027	0.0058	0.0092
速度跟踪误差/(m·s^-1)	0.0011	0.0027	0.0734	0.0966
位置估计误差/m	3.1×10^-16	1.5×10^-14	1.3×10^-5	2.2×10^-5
速度估计误差/(m·s^-1)	1.9×10^-13	6.2×10^-7	3.1×10^-5	5.0×10^-5
加速度估计误差/(m·s^-2)	0	0	0	0
T_u扰动估计误差	0.3529	0.1912	0.0367	0.2274
5T_u扰动估计误差	0.0170	0.0087	0.0182	0.0638

参数	无人机1	无人机2	无人机3	无人机4
位置跟踪误差/m	0.0082	0.0082	0.0058	0.0074
速度跟踪误差/(m·s^-1)	0.0020	0.0068	0.0160	0.0294
位置估计误差/m	7.6×10^-7	1.2×10^-5	0.0165	0.0267
速度估计误差/(m·s^-1)	3.8×10^-6	5.5×10^-5	0.0124	0.0201
加速度估计误差/(m·s^-2)	2.9×10^-5	4.5×10^-4	0.0099	0.0160
T_u扰动估计误差	0.1343	0.0189	0.0241	0.0272
5T_u扰动估计误差	0.0092	0.0162	0.0137	0.0390

参数	无人机1	无人机2	无人机3	无人机4
位置跟踪误差/m	0.0082	0.0082	0.0058	0.0074
速度跟踪误差/(m·s^-1)	0.0020	0.0068	0.0160	0.0294
位置估计误差/m	7.6×10^-7	1.2×10^-5	0.0165	0.0267
速度估计误差/(m·s^-1)	3.8×10^-6	5.5×10^-5	0.0124	0.0201
加速度估计误差/(m·s^-2)	2.9×10^-5	4.5×10^-4	0.0099	0.0160
T_u扰动估计误差	0.1343	0.0189	0.0241	0.0272
5T_u扰动估计误差	0.0092	0.0162	0.0137	0.0390

参数	无人机1	无人机2	无人机3	无人机4
位置跟踪误差/m	0.0231	0.1059	0.1881	0.2698
速度跟踪误差/(m·s^-1)	0.0158	0.0807	0.0613	0.1214
位置估计误差/m	0.0024	0.0208	0.3798	0.6132
速度估计误差/(m·s^-1)	0.0020	0.0138	0.0967	0.1545
加速度估计误差/(m·s^-2)	2.3×10^-16	9.6×10^-15	1.4×10^-6	2.1×10^-6