具有弱通讯的多智能体分布式自适应协同跟踪控制

doi:10.12305/j.issn.1001-506X.2021.02.23

摘要/Abstract

摘要：

针对具有弱通讯的高阶严反馈非线性多智能体系统,提出一种新颖的分布式自适应反演控制方法,并研究了该系统的协同跟踪控制问题。首先,以5个智能体作为被控对象,其中一个智能体以分布式结构组成“领航者-跟随者”编队模式,并且将领航者的运动速度作为整个编队系统的前行速度,其余智能体作为跟随者跟随领航者编队运动。其次,采用自适应反演方法,对系统中由于弱通讯导致的不确定参数进行自适应估计,并对系统设计补偿追踪控制律,使系统中的智能体能够实现自主跟踪时变的参考轨迹,最终以最优的轨迹避开障碍物,并保持期望队形运动。接着,根据Lyapunov稳定性理论,证明了所提方法的有效性。最后,通过仿真对比表明,所提方法能够使多智能体系统的横向、纵向跟踪误差以及参考轨迹的相对误差均实现快速收敛,并在跟踪过程中保持该系统渐近稳定。

关键词: 弱通讯, 多智能体系统, 反推技术, 协同跟踪, 快速收敛

Abstract:

A novel distributed adaptive backstepping control method is proposed for high-order strict feedback nonlinear multi-agent systems with weak communication. And the cooperative tracking control problem of the system is studied. Firstly, five agents are taken as the controlled objects, one of them is formed the "leader follower" formation mode in a distributed structure. The leader's velocity is taken as the forward speed of the whole formation system, and the other agents follow the leader's formation movement as followers. Secondly, the adaptive inversion method is used to estimate the uncertain parameters of the system due to weak communication, and a compensation tracking control law is designed for the system, so that the agents in the system can realize autonomous tracking of time-varying reference trajectory, and avoid obstacles with the optimal trajectory ultimately maintain the desired formation motion. Then, according to Lyapunov stability theory, the effectiveness of the proposed control law is proved. Finally, the simulation results show that the proposed control law can make the lateral and longitudinal tracking errors and the relative errors of the reference trajectory converge rapidly, and keep the system asymptotically stable in the tracking process.

Key words: weak communication, multi-agent system, back-stepping technology, consensus tracking, rapid convergence

中图分类号:

TP237

张普, 薛惠锋, 高山, 左轩. 具有弱通讯的多智能体分布式自适应协同跟踪控制[J]. 系统工程与电子技术, 2021, 43(2): 487-498.

Pu ZHANG, Huifeng XUE, Shan GAO, Xuan ZUO. Distributed adaptive cooperative tracking control of multi-agent system with weak communication[J]. Systems Engineering and Electronics, 2021, 43(2): 487-498.

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智能体编号	(x₀, y₀)/m	(δ_ix, δ_iy)/m	(${\hat \theta } $_ix, ${\hat \theta } $_iy)
智能体#1	(1, 2)	(1, 3)	(3, 6)
智能体#2	(2, 1)	(1, 1)	(5, 2)
智能体#3	(3, 3)	(4, 3)	(4, 3)
智能体#4	(2, 5)	(4, 1)	(7, 1)
智能体#5	(4, 2)	(6, 2)	(10, 4)

方法	稳态误差/m	稳定时间/s
所提方法	0.62	7.1
SMC方法	2.32	16.3
ACM方法	1.61	13.1

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