随机多智能体系统的有限时间多目标环绕控制

针对随机多智能体系统,研究了其多目标有限时间环绕控制问题,其中每个智能体可以跟踪多个目标,但是每个目标只能被一个智能体跟踪.首先,为每个智能体设计了目标状态的估计器,证明了在白噪声干扰之下每个智能体都可以在有限时间内对目标的几何中心位置作出估计.其次,为每个智能体设计了环绕半径的估计器,以及分布式环绕控制器.然后,利用李雅普诺夫有限时间随机稳定性理论,证明了所有智能体在有限时间内能够对环绕半径作出估计,同时可以实现有限时间环绕控制.最后,通过仿真验证了结果的有效性和正确性.     

基于滑模的二阶多智能体快速抗扰一致性

针对带有外部未知扰动的二阶多智能体系统的领导—跟随有限时间一致性问题，本文设计出一种带有时变增益的有限时间干扰观测器，用以实现对每个跟随智能体中未知扰动的快速估计，在此基础上，本文结合超螺旋积分滑模控制方法并利用邻居智能体的位置和速度信息设计一种快速抗扰一致性协议，该协议能够保证存在非线性动态的多智能体系统有限时间一致性控制并能抑制抖振现象.同时，利用李亚普诺夫函数进行了稳定性的证明.最后，通过Matlab数值仿真进一步验证了所提出协议的可行性.     

多智能体系统的旋转目标跟踪控制

介绍对一个旋转目标实现跟踪控制的多智能体系统协调控制问题.提出一个包含领航者及多个跟随者的多智能体系统,该领航者是一个进行匀速圆周运动的智能体,为实现对领航者的跟踪,设计一种能实现旋转跟踪控制的协议,并通过李雅普诺夫方法证明协议能实现旋转目标的跟踪控制.最后,通过数值仿真实验验证了所设计的协议的有效性.     

输入饱和约束下多智能体的有限时间一致

为解决多智能体系统在有限时间跟踪控制过程中受输入饱和影响的问题, 本文研究了输入饱和约束下的 二阶线性多智能体系统的有限时间一致和跟踪控制. 首先在无向通信拓扑下, 利用齐次函数, 设计了基于单饱和函 数的有限时间一致和跟踪控制器. 然后, 应用李雅普诺夫稳定性理论和代数图论等方法证明了控制算法的稳定性. 最后, 给出了能够使多智能体系统实现有限时间一致和跟踪的充分条件. 仿真结果验证了当系统存在输入饱和约束 时, 控制器能使多智能体在有限时间内完成跟踪任务.     

完全分布式异构多智能体系统有限时间跟踪

针对异构二阶非线性多智能体系统有限时间跟踪问题,提出一种完全分布式一致性控制方法,消除对于误差上界与Laplacian矩阵特征值等全局信息的依赖.设计一种只包含局部信息的有限时间一致性协议,并提出自适应增益的分布式切换机制,使得各增益以分段常数的方式进行调节,简化了相邻两次切换时间区间内稳定性分析过程.通过反证法证明多智能体系统必将实现有限时间一致性,并且自适应增益保持有界.仿真结果验证了所提出的完全分布式一致性协议的有效性.     

具有群集行为的时变函数分布式优化

本文对具有群集行为的连续时间多智能体系统的优化问题进行了研究. 考虑具有二阶动力学的多智能体系统, 每个智能体都具有一个局部的时变代价函数. 本文的目标是仅仅依靠局部信息交流使得多智能体在运动的过程中保持 连通性、避免碰撞、总体代价函数最小. 为此本文设计了一种具有群集行为的控制协议, 该协议仅仅依赖于自己和邻居 的速度. 可以证明在该控制协议作用下, 所有智能体在保持连通、避免碰撞的同时, 速度能够跟踪上最优速度. 最后, 通 过一个仿真来说明本文的结果.     

具有群集行为的时变函数分布式优化（英文）

本文对具有群集行为的连续时间多智能体系统的优化问题进行了研究.考虑具有二阶动力学的多智能体系统,每个智能体都具有一个局部的时变代价函数.本文的目标是仅仅依靠局部信息交流使得多智能体在运动的过程中保持连通性、避免碰撞、总体代价函数最小.为此本文设计了一种具有群集行为的控制协议,该协议仅仅依赖于自己和邻居的速度.可以证明在该控制协议作用下,所有智能体在保持连通、避免碰撞的同时,速度能够跟踪上最优速度.最后,通过一个仿真来说明本文的结果.     

二阶多智能体系统参数自适应的有限时间一致性算法

目前二阶多智能体系统尚未明确给出自适应参数的确定方法,且系统的收敛速度较慢.为在实际应用中预测飞行器多智能体系统下一时刻的状态并提高收敛速度,提出一种参数自适应的一致性算法.将当前智能体间位置和速度的差值作为一致性协议的反馈参数,研究固定拓扑和切换拓扑情形下二阶多智能体系统的有限时间一致性问题,构造Lyapunov函数,同时利用LaSalle不变集原理和齐次理论,得到系统在有限时间内达到稳定的条件,实现对不同飞行器输入状态的自适应调节.仿真结果表明,该算法能够保证多智能体系统在有限时间内实现一致跟踪,且收敛速度较快.     

基于迭代学习的部分非正则多智能体编队控制

针对一类具有任意初始状态的部分非正则多智能体系统,提出一种迭代学习控制算法.该算法将具有固定拓扑结构的多智能体编队控制问题转化为广义上的跟踪问题,即让领导者跟踪给定的期望轨迹,而跟随者要始终保持预定队形对某一智能体进行跟踪,并将该智能体作为自身的领导者.同时,为了使每个智能体在任意初始状态下都能按照期望队形进行编队,对每个智能体的初始状态设计迭代学习律,并从理论上对算法的收敛性进行严格证明,给出算法收敛的充分条件.所提出的算法对于各个智能体在任意初始位置条件下均能实现在有限时间区间内系统的稳定编队.最后,通过仿真算例进一步验证了所提出算法的有效性.     

输出饱和多智能体系统的迭代学习趋同跟踪控制

针对带有输出饱和的多智能体系统有限时间趋同跟踪控制问题,提出了一种分布式迭代学习控制算法.首先假设多智能体系统具有固定拓扑结构,且仅有部分智能体可获取到期望轨迹信息.基于输出约束条件构造一致性跟踪误差,在此基础上设计了P型迭代学习控制率.然后采用压缩映射方法给出了一个算法收敛的充分条件,并在理论上证明了跟踪误差的收敛性.最后,将理论结果推广至具有随机切换拓扑结构的多智能体系统中.仿真结果验证了所提出算法的有效性.     

Finite-time circle surrounding control for multi-agent systems

In this paper, a finite-time circle surrounding control problem for multi-agent systems is investigated. The objective is to make all the surrounding agents eventually distribute on a circle uniformly and all the target agents surrounded by this circle in the finite time. Both a distributed estimator and a distributed control protocol are presented to achieve such a goal. Firstly, an estimator of the targets’ geometric center is used to estimate the center of targets. Secondly, a distributed control protocol is proposed for each surrounding agent by using the value of the estimator to guarantee all the surrounding agents uniformly distribute on a circle and all the target agents are surrounded by this circle in the finite time. Then it is proved that the control goal can be achieved in the finite time. Finally, a simulation example is given to show the effectiveness of the proposed method.     

Finite-time consensus for multi-agent systems via nonlinear control protocols

This paper investigates the fnite-time consensus problem of multi-agent systems with single and double integrator dynamics,respectively.Some novel nonlinear protocols are constructed for frst-order and second-order leader-follower multi-agent systems,respectively.Based on the fnite-time control technique,the graph theory and Lyapunov direct method,some theoretical results are proposed to ensure that the states of all the follower agents can converge to its leader agent s state in fnite time.Finally,some simulation results are presented to illustrate the efectiveness of our theoretical results.     

Finite-time consensus protocols for networks of dynamic agents by terminal iterative learning

This paper aims to address finite-time consensus problems for multi-agent systems under the iterative learning control framework. Distributed iterative learning protocols are presented, which adopt the terminal laws to update the control input and are offline feedforward design approaches. It is shown that iterative learning protocols can guarantee all agents in a directed graph to reach the finite-time consensus. Furthermore, the multi-agent systems can be enabled to achieve a finite-time consensus at any desired terminal state/output if iterative learning protocols can be improved by introducing the desired terminal state/output to a portion of agents. Simulation results show that iterative learning protocols can effectively accomplish finite-time consensus objectives for both first-order and higher order multi-agent systems.     

Distributed robust finite-time nonlinear consensus protocols for multi-agent systems

This paper investigates the robust finite-time consensus problem of multi-agent systems in networks with undirected topology. Global nonlinear consensus protocols augmented with a variable structure are constructed with the aid of Lyapunov functions for each single-integrator agent dynamics in the presence of external disturbances. In particular, it is shown that the finite settling time of the proposed general framework for robust consensus design is upper bounded for any initial condition. This makes it possible for network consensus problems to design and estimate the convergence time offline for a multi-agent team with a given undirected information flow. Finally, simulation results are presented to demonstrate the performance and effectiveness of our finite-time protocols.     

多智能体多目标跟踪算法研究

研究了多智能体同时跟踪多个目标的群集算法,采用智能体的编号对目标数求余数的方法来确定各个智能体的跟踪目标。对于势场函数,根据智能体目标是否相同建立了两种势场函数,并在此基础上确定动态系统的控制输入,使相同目标的智能体在跟踪目标的过程中形成群集,而不同目标的智能体相互分离;用李亚普诺夫稳定性理论分析了算法的收敛性。仿真结果表明,所提算法可有效解决多目标跟踪问题。     

Finite-time consensus tracking for multi-agent systems with inherent uncertainties and disturbances

In this paper, finite-time consensus tracking is investigated via time-varying feedback for uncertain nonlinear multi-agent systems (NMASs). The presence of inherent uncertainties and disturbances in the NMASs highlights the main novelty : (1) The inherent uncertainties imply that more serious unknowns and time-variations are allowed in the nonlineartities and the control coefficients of the NMASs. (2) The inherent disturbances mean that the upper bound of the disturbances is unknown. To compensate the inherent uncertainties and disturbances, time-varying protocols are proposed by integrating time-varying technique and sliding mode method. Based on the proposed protocols, the finite-time leader-following consensus and finite-time containment are achieved under directed graph. Finally, the validation of the proposed protocols is verified by two examples.     

基于事件触发非线性多智能体系统的固定时间一致性

本文研究了在有向拓扑下,带有非线性动力学多智能体系统的固定时间一致性问题.提出了一种新的基于事件触发机制的非线性控制策略,对于每个智能体给出了基于状态信息的事件触发条件,当状态误差满足所给条件时才触发事件,能有效的减小系统的能量耗散和控制器的更新频次.利用Lyapunov稳定性理论和代数图论,证明在该控制策略下,多智能体系统在固定时间能实现领导跟随一致性,且不存在Zeno行为.相较于有限时间一致性策略,采用固定时间一致性策略系统的收敛时间不再依赖于系统的初始状态.最后,仿真实例验证了理论结果的有效性.     

Bipartite tracking of homogeneous and heterogeneous linear multi-agent systems

In this paper, we consider bipartite tracking of linear multi-agent systems with a leader. Both homogeneous and heterogeneous systems are investigated. The communication between agents is modelled by a directed signed graph, where the negative (positive) edges represent the antagonistic (cooperative) interactions among agents. Linear Quadratic Regulator (LQR)-based approach is used to derive the distributed protocol for the follower agent to achieve bipartite tracking of the leader. It is shown that solving the bipartite tracking problem over the structurally balanced signed graph is equivalent to solving the cooperative tracking problem over a corresponding graph with nonnegative edge weights. This bridges the gap between the newly raised bipartite tracking problem and the well-studied cooperative tracking problem. Three novel control protocols are proposed for both cooperative and bipartite output tracking of heterogeneous linear multi-agent systems. Numerical examples are given to show the effectiveness of our control protocols.     

线性和非线性动态异构多自主体系统的有限时间一致性（英文）

In this paper, the finite-time consensus problems of heterogeneous multi-agent systems composed of both linear and nonlinear dynamics agents are investigated. Nonlinear consensus protocols are proposed for the heterogeneous multi-agent systems.Some sufficient conditions for the finite-time consensus are established in the leaderless and leader-following cases. The results are also extended to the case where the communication topology is directed and satisfies a detailed balance condition on coupling weights.At last, some simulation results are given to illustrate the effectiveness of the obtained theoretical results.     

线性和非线性动态异构多自主体系统的有限时间一致性

研究了由线性和非线性动态自主体组成的异构多自主体系统的有限时间一致性问题.针对该异构系统提出了非线性的一致性协议,并分别给出了无领航者和有领航者情形下异构系统在有限时间内实现一致性的充分条件.所得结果还推广到具有有向通信拓扑且满足细致平衡条件的多自主体系统情形.最后,给出一些仿真结果来验证所得结论的正确性和有效性.