基于事件触发的多智能体系统预设时间编队控制

doi:10.12382/bgxb.2024.0292

摘要/Abstract

摘要：

为解决编队控制存在的收敛速度慢、控制器连续更新问题,针对2阶多智能体系统,提出一种基于事件触发机制的预设时间编队控制方法。基于预设时间的加速度观测器,跟随者于预设时间内估计到领航者的加速度状态。设计基于事件触发机制的预设时间编队控制器使跟随者于预设时间内跟踪上领航者,避免了控制器的连续更新。基于严格的理论分析证明,多智能体系统可实现预设时间编队控制,且避免芝诺现象。数值仿真结果表明,新提出的基于事件触发的预设时间编队控制方法可使多智能体系统于指定时间内形成期望构型,同时降低控制器更新频率从而降低系统能耗。基于四旋翼无人机编队飞行试验结果,进一步验证了新提出的控制方法的可用性和拓展性。

关键词: 多智能体系统, 编队控制, 预设时间控制, 事件触发机制, 四旋翼无人机

Abstract:

To solve the problems of slow convergence rate and continuous controller updates in formation control, this paper proposes a prescribed-time formation control method based on event-triggering mechanism for second-order multi-agent systems.Based on a prescribed-time acceleration observer, the followers can estimate the acceleration state of leader within the prescribed time.Moreover, a prescribed-time formation controller based on the event-triggering mechanism is designed to enable the followers to keep up with the leader within the prescribed time.The event-triggering mechanism proposed avoids the continuous updates of controller.Through the rigorous theoretical analysis, it is proved that the proposed method can be used to achieve the prescribed-time formation control for the multi-agent systems without Zeno behavior.Simulated results indicate that the proposed prescribed-time formation control method based on the event-triggering mechanism can make the multi-agent systems form a desired formation configuration within a preset time, and reduce the update frequency of controller to save resources.The feasibility and extensibility of the proposed control method are further verified based on the formation flight test results of quadrotor UAVs.

Key words: multi-agent system, formation control, prescribed-time control, event-triggering mechanism, quadrotor unmanned aerial vehicle

中图分类号:

TP13

侯天乐, 毕文豪, 黄湛钧, 李铭浩, 张安. 基于事件触发的多智能体系统预设时间编队控制[J]. 兵工学报, 2025, 46(4): 240292-.

HOU Tianle, BI Wenhao, HUANG Zhanjun, LI Minghao, ZHANG An. Prescribed-time Formation Control with Event-triggering Mechanism for Multi-agent Systems[J]. Acta Armamentarii, 2025, 46(4): 240292-.

图/表 20

图1 算例1的通信拓扑(算例1)

Fig.1 Communication topology (Example 1)

表1 多智能体系统初始状态(算例1)

Table 1 The initial states of MASs (Example 1)

智能体	p_i/m	v_i/(m·s^-1)	a_i/(m·s^-2)
0	-1	0
1	10	-1	0
2	2	-2	0.5
3	-10	3	0
4	5	1	1
5	-3	2	-1
6	3	-3	0

图2 智能体加速度估计量轨迹

Fig.2 Estimated acceleration trajectories of agents

图3 跟随者位置跟踪误差轨迹

Fig.3 Position tracking error trajectories of followers

图4 跟随者速度跟踪误差轨迹

Fig.4 Velocity tracking error trajectories of followers

图5 跟随者控制输入轨迹

Fig.5 Control input trajectories of followers

表2 采用事件触发机制与未采用事件触发机制控制器更新次数比较(算例1)

Table 2 Comparison of update frequencies of controller with and without event-triggering mechanism (Example 1)

类别	跟随者智能体
类别	1	2	3	4	5	6
采用事件触发机制	999	853	843	964	860	970
未采用事件触发机制	5000

表3 算法参数(算例2)

Table 3 Algorithm parameters (Example 2)

算法	算法参数
文献[32]算法	k₁=1.2,k₂=0.3,k₃=0.5,k₄=0.8,k₅=3.5,k₆=2,a=1,b=2,β=1.5,l₁=0.1,l₂=0.3,ρ=0.2
本文算法	k₁=1,δ=1,h₁=2,α₁=2,k₂=30,k₃=15,h₂=5,α₂=8,γ=5,T₁=0.5

图6 总跟踪误差轨迹(算例2)

Fig.6 Total tracking error trajectories (Example 2)

图7 跟随者控制输入轨迹(算例2)

Fig.7 Control input trajectories of followers (Example 2)

图8 总跟踪误差轨迹(算例3)

Fig.8 Total tracking error trajectories (Example 3)

表4 采用事件触发机制与未采用事件触发机制控制器更新次数比较(算例3)

Table 4 Comparison of update frequencies of controller with and without event-triggering mechanism (Example 3)

算法	跟随者智能体
算法	1	2	3	4	5	6
本文算法	707	694	663	680	638	663
文献[24]算法	3000

图9 试验平台示意图

Fig.9 Hardware platform

图10 四旋翼无人机编队通信拓扑

Fig.10 Communication topology of quadrotor UAVs

表5 无人机初始位置与速度

Table 5 The initial position and velocity of UAVs

无人机	p_i/m	v_i/(m·s^-1)	a_i/(m·s^-2)
0	[0,1,0]^T	[0,0,0]^T
1	[2.5,1,0]^T	[0,0,0]^T	[0,0,0]^T
2	[2.5,-1.5,0]^T	[0,0,0]^T	[0,0,0]^T
3	[0,-1.5,0]^T	[0,0,0]^T	[0,0,0]^T

图11 编队飞行示意图

Fig.11 formation flight

图12 飞行轨迹

Fig.12 Flight trajectories

图13 位置跟踪轨迹

Fig.13 Position tracking trajectories

图14 速度跟踪轨迹

Fig.14 Velocity tracking trajectories

表6 事件触发机制下触发次数

Table 6 The triggering frequency with the event triggering mechanism

跟随者无人机	x轴方向	y轴方向	z轴方向
1	251	264	243
2	323	288	281
3	312	292	284

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