PDE-based event-triggered containment control of multi-agent systems with input delay under spatial boundary communication

This article studies the containment control problem for multi-agent systems with input delay under spatial boundary communication by employing an event-based approach. Firstly, the collective dynamics of multi-agent systems are described as parabolic partial differential equations (PDEs). Applying the integral transformation method developed in PDEs, the delayed parabolic PDEs are transformed into a series of new coupled PDE-PDE systems. Then, by taking the spatial boundary communication scheme into account and using the local boundary information, two boundary containment control protocols together with a dynamic event-triggered scheme (DETS) are designed, such that the states of all followers converge to a convex hull formed by multiple leader agents with and without input delay. The optimal protocols are given by minimizing the 2-norm of the designed control gain matrix, and the exclusion of the Zeno behavior is analyzed. Finally, a numerical simulation example is provided to support the main results.     

Circle formation control for multi-agent systems with a leader

In this paper, we focus on circle formation control of multi-agent systems (MAS) with a leader. The circle formation is achieved based on the lead-following and the artificial potential field method. A...     

Decentralised control for formation reorganisation of multi-agent systems using a virtual leader

In this article, we study the topology reorganisation of formations for multi-agent systems with a broken agent during motion. The cases with a broken agent in different topologies and different positions are studied, and a decentralised algorithm is proposed to reorganise the different damaged topologies of formations. The main contributions of this article include: first, a collective potential function model is designed to reorganise the topologies, and a repulsive potential function model is proposed to avoid obstacles; second, a decentralised algorithm based on potential functions is presented; third, a virtual agent is designed to be a leader as soon as an agent is damaged, and disappears once the topology is repaired. Finally, some simulation results are studied to demonstrate the efficiency of the proposed algorithm.     

Backstepping in Infinite Dimension for a Class of Parabolic Distributed Parameter Systems

 In this paper a family of stabilizing boundary feedback control laws for a class of linear parabolic PDEs motivated by engineering applications is presented. The design procedure presented here can handle systems with an arbitrary finite number of open-loop unstable eigenvalues and is not restricted to a particular type of boundary actuation. Stabilization is achieved through the design of coordinate transformations that have the form of recursive relationships. The fundamental difficulty of such transformations is that the recursion has an infinite number of iterations. The problem of feedback gains growing unbounded as the grid becomes infinitely fine is resolved by a proper choice of the target system to which the original system is transformed. We show how to design coordinate transformations such that they are sufficiently regular (not continuous but L _∞). We then establish closed-loop stability, regularity of control, and regularity of solutions of the PDE. The result is accompanied by a simulation study for a linearization of a tubular chemical reactor around an unstable steady state. Date received: June 22, 2001. Date revised: January 17, 2002. RID="*" ID="*"This work was supported by grants from AFOSR, ONR, and NSF.     

基于预估器的一类多智能体系统神经动态面输出一致控制

本文针对一类含未知扰动与非对称输入饱和的非线性多智能体系统,提出基于预估器的神经动态面输出一致控制策略.在设计预估器的基础上构造预估误差,驱动神经网络更新权值估计系统未知动态,并将预估器与神经网络应用于非线性扰动观测器来补偿广义扰动.本文所提出的控制策略采用神经网络权值范数学习方法,减少学习参数数目.对于非对称的输入饱...     

Distributed formation control of fractional-order multi-agent systems with absolute damping and communication delay

The distributed formation control of fractional-order multi-agent systems is mainly studied under directed interaction topology in this paper. First, the control algorithm with absolute damping and communication delay is proposed to achieve the formation control. Then, some sufficient conditions are derived by using the matrix theory, graph theory and the frequency-domain analysis method. Finally, based on the numerical method of predictor–corrector, several simulations are presented to illustrate the effectiveness of the obtained results.     

多智能体系统编队控制相关问题研究综述

首先梳理了编队控制研究的脉络, 介绍了3 种经典的编队控制方法, 即跟随领航者法、基于行为法和虚拟结构法的研究思想; 接着综述了近年来发展的, 包容了上述3 种方法且基于图论的编队控制理论的研究成果, 包括多智能体系统图论的建模, 基于代数图论和基于刚性图论的多智能体编队控制律设计、编队构型变换等方面的研究成果; 然后从图论结果出发, 回顾了与编队控制密切相关的一致性、聚集/同向、群集/蜂拥和包络控制的最新进展; 最后, 为了促进多智能体系统在实际中的应用, 指出了多智能体编队控制研究中有待解决的若干问题.

     

具有执行器故障的不确定多智能体系统自适应动态面控制

本文研究了一类具有输入量化、未建模动态和执行器故障的非线性多智能体系统的一致跟踪问题.引入一个可量测的动态信号消除未建模动态对系统的影响.利用Young’s不等式和高斯函数的性质,有效地处理了多智能体邻居节点在设计的第一步中对子系统的耦合作用.通过将滞回量化器表示为具有有界系数和有界扰动的输入线性函数,并利用动态面控制方法,提出一种自适应神经网络动态面控制方案,简化了控制器的设计,保证了闭环系统的所有信号都是半全局一致终结有界的,所有跟随者都能实现期望的一致性.最后,仿真结果验证了所提出的自适应控制策略的有效性.     

Distributed adaptive control for time-varying formation of general linear multi-agent systems

An adaptive gain scheduling technique is investigated to discuss distributed time-varying formation (TVF) control problems for general linear time-invariant multi-agent systems (LTI-MASs), where two types of topologies are considered: (1) the interaction topology is undirected and connected, and (2) the interaction topology is directed. Two fully distributed adaptive TVF control protocols are, respectively proposed, which both assign a time-varying coupling weight to each node in the interaction topology. Two algorithms to design the constructed protocols are presented under the undirected and directed interaction topologies, respectively. A feasible TVF set is provided. The stabilities of two algorithms are, respectively proved based on the Lyapunov functional theory. For both undirected and directed interaction topologies, general LTI-MASs can achieve the given TVF using the designed fully distributed adaptive formation protocol without any global information about the interaction topology when the TVF satisfies the feasible set. Finally, theoretical results are illustrated with numerical simulation examples.     

Minimum-energy time-varying formation of distributed multi-agent systems with interaction constraints

In the current paper, minimum-energy time-varying formation design and analysis problems of distributed multi-agent systems (DMASs) subjected to randomly switching topologies and aperiodic interaction pauses are investigated, which can ensure the time-varying formation achievement with the minimum-energy consumption in the sense of the linear matrix inequality. Firstly, a formation control protocol is designed with local information of neighboring agents, where the total energy consumption during the formation process is constructed and the impacts of interaction constraints are imposed. Then, minimum-energy formation design and analysis criteria of DMASs are presented in terms of the linear matrix inequality tool, which can be checked by the generalized eigenvalue method. Finally, a numerical simulation is shown to verify the effectiveness of the main results.     

通信时滞下事件驱动多智能体系统环形编队控制

针对一阶具有通信时滞的多智能体系统环形编队存在通信和计算资源消耗大的问题,引入事件驱动控制机制,综合设计适用于任意环形编队的控制律分别耦合状态相关和状态无关两类事件驱动条件。事件触发函数基于状态误差建立,使得个体之间的信息通信和控制信号更新仅在事件触发时刻进行。从理论上严格证明了系统在控制律作用下的收敛性,并通过数值仿真验证了控制算法的有效性。仿真结果也表明,在获得系统期望性能的前提下,降低了控制器输入的更新频率和减少了智能体的资源消耗。     

Bearing-based formation stabilization using event-triggered control

This article studies two distributed bearing-based event-triggered schemes to achieve formation stabilization. We focus on systems with double-integrator dynamics with bearings sensing capabilities. Firstly, we propose a bearing-only event-triggered condition (ETC) that is edge-dependent which drives the control updates of the agents using only information dependent on relative sensed quantities. Secondly, along with bearing measurements we make use of local agent state measurements to arrive at an ETC that uses this collective measurement to drive the sensing and control updates of an agent. In doing so, we propose a new control law that renders the final formation stationary. Simulations are provided to verify the validity of the proposed algorithms.     

Event-based broadcasting containment control for multi-agent systems under directed topology

The event-based broadcasting containment control problem for both first-order and second-order multi-agent systems under directed topology is investigated. Based on certain event, each agent decides when to transmit its current states to its neighbours and the agents’ distributed control algorithms are based on these sampled state measurements, which can significantly decrease the number of the controllers’ updates. All the agents are divided into two groups, namely, the leaders and the followers. The formation control is introduced. The leaders exchange their information to converge to a formation. The followers utilise the information from both their leader neighbours and their follower neighbours and are driven to the convex hull of the leaders using the proposed control algorithms. Numerical simulations are provided to illustrate the effectiveness of the obtained theoretical results.     

具有时变时滞耦合的二阶多主体系统的编队控制

多主体系统的编队控制是一类重要的网络协同控制问题.研究了在有向连接拓扑结构下,具有时变时滞耦合的二阶多主体系统的编队控制问题.通过一种多层领导机制的框架建模,得到了时不变编队、时变编队和时变轨迹追踪3种编队问题的充分性条件,并证明了各种预期队列是以指数的收敛速度形成的.数值仿真进一步验证了理论结果的正确性,为该理论在实际中应用起到指导作用.     

Finite-time formation control for multi-agent systems

In this paper, we develop a new finite-time formation control framework for multi-agent systems with a large population of members. In this framework, we divide the formation information into two independent parts, namely, the global information and the local information. The global formation information decides the geometric pattern of the desired formation. Furthermore, it is assumed that only a small number of agents, which are responsible for the navigation of the whole team, can obtain the global formation information, and the other agents regulate their positions by the local information in a distributed manner. This approach can greatly reduce the data exchange and can easily realize various kinds of complex formations. As a theoretical preparation, we first propose a class of nonlinear consensus protocols, which ensures that the related states of all agents will reach an agreement in a finite time under suitable conditions. And then we apply these consensus protocols to the formation control, including time-invariant formation, time-varying formation and trajectory tracking, respectively. It is shown that all agents will maintain the expected formation in a finite time. Finally, several simulations are worked out to illustrate the effectiveness of our theoretical results.     

分布式离散多智能体系统在固定和切换拓扑下的编队控制

研究多智能体系统在分布式采样控制下固定拓扑和时变通信拓扑时的追踪和编队问题. 首先分析目标系统 在没有输入时的稳定性; 然后分别给出在固定和时变通信拓扑下使各智能体完成追踪和编队的控制协议, 并给出了系统稳定时采样间隔需满足条件的充分性和必要性证明; 最后通过仿真研究验证了所提出算法的有效性.

     

Finite-time optimal formation control of multi-agent systems on the Lie group SE(3)

This paper investigates the finite-time optimal formation problem of multi-agent systems on the Lie group SE(3), for the situation when the formation time and/or the cost function need to be considered. Under the condition that the formation time is given according to the task requirement, a finite-time optimal formation controller is proposed for the two-agent case to guarantee that the desired formation is achieved at the given time and the corresponding cost function is optimal. For the systems with multiple agents, the obtained finite-time optimal formation control law has second-order approximation accuracy. Finally, some numerical simulations are provided to illustrate the effectiveness of the theoretical results.     

基于模糊人工势场法的多智能体编队控制及避障方法

针对动态环境中多智能体编队控制及避障问题,提出了一种基于模糊人工势场法的编队方法。首先,在领航跟随法的框架下控制编队队形,在动态队形变换策略的异构模式下,使用人工势场法为多智能体编队中每个智能体规划避障路径;其次,利用模糊控制器控制跟随智能体追踪领航智能体,同时保持跟随智能体之间与领航智能体的相对距离,遇到未知障碍物时,及时保持多智能体编队之间的队形并避免碰撞障碍物。针对人工势场法在引力增量系数和斥力增量系数设置的局限性,利用模糊控制器选择出适应环境的增量系数。Matlab仿真实验结果表明,该方法能够有效地解决复杂环境下多智能体编队控制及避障问题,使用效率函数对实验数据进行分析,验证了所优化方法的合理性和有效性。     

事件驱动的强化学习多智能体编队控制

针对经典强化学习的多智能体编队存在通信和计算资源消耗大的问题,本文引入事件驱动控制机制,智能体的动作决策无须按固定周期进行,而依赖于事件驱动条件更新智能体动作。在设计事件驱动条件时,不仅考虑智能体的累积奖赏值,还引入智能体与邻居奖赏值的偏差,智能体间通过交互来寻求最优联合策略实现编队。数值仿真结果表明,基于事件驱动的强化学习多智能体编队控制算法,在保证系统性能的情况下,能有效降低多智能体的动作决策频率和资源消耗。