网络化热方程的集中事件触发控制

本文对热方程建模的分布式参数化多智能体系统进行研究,设计了基于事件触发控制下的一致性边界控制器,将网络化热方程的状态驱动到相同的稳定状态.其中每一个子系统的边界信息能被测量,并且所有的智能体由无向静态拓扑连接.事件触发控制器由以下两部分组成:一是基于网络拓扑的边界局部交互作用,驱动所有子系统达到相同的状态;二是由事件触发条件建立的触发时刻.本文证明了在事件触发的边界一致性控制下两个连续触发时刻之间存在最小停留时间以避免Zeno现象;同时利用李雅普诺夫函数分析并保证了闭环系统的稳定性和适定性.最后,给出了由5个热方程组成的多智能体系统的仿真算例,结果证实了本文所设计事件触发控制器的真实性.     

基于事件触发的时变拓扑多智能体系统编队控制

针对资源受限的时变拓扑多智能体系统的编队控制问题,提出一种基于复合误差信息事件触发机制以减少不必要的信息传输,降低带宽占用,并设计了多智能体系统的编队控制协议和分布式事件触发机制.通过将多智能体系统的编队控制问题转化为闭环延时系统的稳定性问题,构造Lyapunov-Krasovskii函数并利用线性矩阵不等式技术,给出多智能体系统实现编队的充分条件.最后,通过仿真验证了所提出方法的有效性.     

基于事件触发机制的多智能体网络平均一致性研究

文章研究了事件触发机制下具有固定和切换拓扑结构的多智能体网络的平均一致性问题。为了有效降低多智能体一致性控制协议的更新次数,文章提出了仅依赖于各智能体及其邻居节点信息的分布式事件触发机制。为了使多智能体网络渐近收敛至初始平均状态,文章提出了基于事件触发机制的多智能体平均一致性协议。然后,文章建立了事件触发机制下的闭环系统模型,并分别获得了固定和切换拓扑结构下多智能体网络平均一致收敛的充分条件。仿真表明,基于事件触发机制的平均一致性协议保证了多智能体网络的平均一致性,并且分布式事件触发机制有效降低了多智能体一致性协议更新次数。     

基于事件触发的拓扑切换异构多智能体协同输出调节

研究切换拓扑下线性异构多智能体系统的协同输出调节问题,并设计了一个基于事件触发的输出调节控制机制.设计的控制机制不仅可以实现智能体对外部系统的渐近跟踪和干扰抑制,还可以有效减少智能体之间的信息传递数量,从而降低通信负载减少网络能耗.最后通过仿真验证结论的有效性.     

基于自触发的异构多智能体协同输出调节

本文针对线性异构多智能体系统,基于自适应自触发条件,分别设计了状态和输出反馈协同控制器.其中自适应控制策略可以避免使用多智能体系统的全局信息,从而实现分布式控制;自触发控制不仅可以避免对触发条件进行连续监测,还可以有效地降低网络的通信负载和控制器的更新次数,且不存在芝诺现象.最后通过4个跟随智能体和一个领导智能体进行了协同输出直角编队仿真实验,实现了多智能体系统对外部系统的渐近跟踪和干扰抑制,验证了结果的有效性.     

基于事件触发的离散多智能体二分一致性

针对一阶离散多智能体系统,研究了事件触发控制下的二分一致性问题.首先考虑智能体间通信拓扑结构为无向连通结构平衡图的情形,针对各智能体设计事件触发控制,包括仅依赖于自身及邻居智能体采样状态的控制输入,以及仅依赖自身状态的事件触发条件,实现了对通信资源的节约利用.基于图论、离散系统稳定性理论,证明系统能够实现二分一致性.同时,合理设置控制输入及事件触发条件中参数,保证系统不存在Zeno现象.之后,进一步分析设计了包含有向生成树的结构平衡图下,多智能体系统的事件触发控制.最后利用仿真实例验证了理论结果的有效性.     

积分事件触发策略下的线性多智能体系统领导跟随一致性

研究有向切换拓扑下线性多智能体系统的事件触发一致跟踪问题.大多数已有的工作研究了固定拓扑下的事件触发控制,然而,当智能体间联系随时间发生改变或通信拓扑随时间发生变化时,该控制策略失效.鉴于此,在考虑切换拓扑的基础上提出一种基于积分型事件触发的控制策略.首先,当拓扑图包含一棵生成树且领导者是根节点时,利用Lyapunov稳定性理论、代数图论和矩阵变换,基于积分型事件触发控制协议,在切换拓扑下多智能体系统达到领导跟随一致性;然后,当存在多个领导者时,基于设计的触发机制在切换拓扑下多智能体系统实现包含控制,上述两种情况下闭环系统均不存在Zeno现象;最后,通过仿真结果验证控制策略的有效性.     

带有不匹配干扰的多智能体系统有限时间积分滑模控制

针对动态多智能体系统协同控制问题，本文研究了带有不匹配干扰的二阶多智能体系统的有限时间包容控制，提出了基于非线性积分滑模控制（Integral sliding-mode control，ISMC）的复合分布式包容控制算法.首先利用Lyapunov稳定性和齐次性定理，分析了未受扰系统的有限时间包容控制问题；然后针对存在不匹配干扰的多智能体动态系统，设计非线性有限时间干扰观测器估算智能体的状态和干扰，提出基于干扰观测器的复合分布式积分滑模控制协议，结合现代控制理论和滑模控制理论，研究了带有不匹配干扰的多智能体系统有限时间包容控制问题.最后数值仿真证明了控制算法的有效性.     

分布式事件触发多自主体领导跟随一致性研究

为了提高系统的通信效率和能源利用率,减少多自主体系统硬件资源的浪费,提出了只需要自主体自身及其最近邻居节点信息的分布式事件触发控制算法。研究了带有动态领导者的二阶多自主体系统领导跟随一致性问题。应用矩阵论和现代控制理论研究了在分布式事件触发机制下的二阶系统,得到了基于事件触发机制的多自主体系统协同运动的收敛条件。通过理论分析与计算表明,在此控制协议下不会存在芝诺行为,并且多自主体系统可以实现领导跟随一致性。最后,应用计算机仿真验证了本文所提控制协议的可靠性。     

随机多智能体系统的多率协同控制

本文针对一类带有非线性动力学的随机多智能体系统研究了基于多率采样机制的一致性控制问题。首先,引入多率采样机制异步地对智能体的状态进行采样,并且使用缓存器来同步智能体不同分量的状态信息。然后,提出了一种基于边的事件触发传输机制将每个智能体的状态信息定向传输给邻居智能体,从而减少了通信资源的使用和控制器的更新频率。接着,本文根据所设计的事件触发传输机制设计了相应的控制协议使得随机多智能体系统可以实现均方一致性。因为每条边上的事件都是独立发生的,所以智能体的邻居之间不需要保证信息的时钟同步。最后,给出了数值仿真例子。通过将同步采样机制、异步采样机制和多率采样机制进行比较,说明了所提出的边事件触发传输机制在多率采样下可以获得更好的系统性能。     

Event-triggered based bearing-only formation control for nonlinear multi-agent with unknown disturbance

This article delves into the bearing-only formation tracking control problem of nonlinear multi-agent systems with unknown disturbances and unmodeled dynamics, wherein the distributed control solely utilizes the relative bearing information of its neighbors. Firstly, a disturbance observer combined with a neural network is proposed to eliminate the impact of unknown disturbances and unmodeled dynamics. Additionally, a pioneering event-triggered based backstepping control approach is put forth for the formation tracking control problem of nonlinear multi-agent systems, which economizes on communication bandwidth and computing resources by decreasing the update frequency of the controller. Finally, using the Lyapunov method, it is demonstrated that all signals of the control system are bounded, and the convergence errors are confined to a small neighborhood of the origin while excluding the “Zeno behavior” phenomenon through rigorous proof.     

带有不匹配干扰的二阶多自主体系统有限时间包容控制

针对多自主体系统群集运动问题,本文研究了带有不匹配干扰的二阶系统有限时间包容控制.运用现代控制理论,设计了非线性观测器,对系统未知状态和干扰进行估计.在状态估计的基础上,构建了基于干扰观测器的多自主体系统的协同控制算法.应用代数图论和齐次性理论等方法,分析了二阶多自主体系统有限时间包容控制.数据仿真中应用基于观测器的包容控制算法,使得系统的运动状态最终都收敛到由多个领导者所围成的目标区域中,验证了本文结果的有效性.     

Observer-based prescribed-time consensus control for heterogeneous multi-agent systems under directed graphs

This work studies the prescribed-time robust consensus tracking problem of heterogeneous multi-agent systems over directed graphs. Aiming at multi-agent systems with a static leader and only matched disturbances, a distributed observer-based consensus algorithm is developed, to ensure that the tracking errors converge to zero accurately in prescribed time. For the case of multi-agent systems with a dynamic leader and mismatched/matched disturbances, an adaptive strategy based on a distributed observer and a disturbance observer is designed by the dynamic damping reciprocal technology. Such strategy can avoid the numerical singularity, adapt to the situation that the upper bounds of the disturbances are unknown, and assure that the tracking errors converge to an adjustable neighborhood of zero within prescribed time. Finally, simulations are given to verify the effectiveness of the proposed control strategies.     

具有外部干扰的二阶多自主体系统的协同运动

为解决多自主体系统在群集运动过程受到外部干扰影响的问题,本文研究了具有外部干扰的二阶多自主体系统的分布式协同控制.本文中的外部干扰包括匹配干扰和不匹配干扰,针对系统中的匹配干扰,设计了状态观测器和干扰观测器,对系统的未知状态和干扰进行估计,并且构造了基于干扰观测器的多自主体协同控制算法.对于系统中的不匹配干扰,设计了与匹配干扰不同的干扰观测器,构造了基于主动抗干扰观测器的协同控制算法.运用矩阵论和现代控制理论等方法,研究了基于干扰观测器的二阶多自主体系统的协同控制.应用计算机仿真分别验证在多自主体系统具有匹配干扰和不匹配干扰的情况下结论的有效性,仿真结果表明,本文所设计的多自主体协同控制算法可以使跟随者最终都收敛到领导者的状态,实现了具有匹配干扰和不匹配干扰的二阶多自主体系统的状态一致性.     

Decentralised consensus for multiple Lagrangian systems based on event-triggered strategy

This paper considers the decentralised event-triggered consensus problem for multi-agent systems with Lagrangian dynamics under undirected graphs. First, a distributed, leaderless, and event-triggered consensus control algorithm is presented based on the definition of generalised positions and velocities for all agents. There is only one triggering function for both the generalised positions and velocities and no Zeno behaviour exhibited under the proposed consensus strategy. Second, an adaptive event-triggered consensus control algorithm is proposed for such multi-agent systems with unknown constant parameters. Third, based on sliding-mode method, an event-triggered consensus control algorithm is considered for the case with external disturbance. Finally, simulation results are given to illustrate the theoretical results.     

Observer-based event-triggered distributed model predictive control for a class of nonlinear interconnected systems

In this paper, an observer-based event-triggered distributed model predictive control method is proposed for a class of nonlinear interconnected systems with bounded disturbances, considering unmeasurable states. First of all, the state observer is constructed. It is proved that the observation error is bounded. Second, distributed model predictive controller is designed by using observed value. Meanwhile, the event-triggered mechanism is set by using the error between the actual output and the predicted output. The setting of event-triggered mechanism not only ensures the error between the actual output and the predicted output within a certain range, but also reduces the calculation amounts of solving the optimization problem. The states of each subsystem enter the terminal invariant set by distributed model predictive control, and then are stabilized in the invariant set under the action of output feedback control law. In addition, sufficient conditions are given to ensure the feasibility of the algorithm and the stability of the closed-loop system. Finally, the numerical example is given, and the simulation results verify the effectiveness of the proposed algorithm.     

Adaptive Event-triggered Control for Stochastic Nonlinear Multi-agent Systems with Unknown Control Directions

This paper focuses on the adaptive event-triggered consensus control problem for a class of stochastic nonlinear multi-agent systems with unknown nonlinear control directions and external disturbances. The heterogeneous nonlinear dynamics and non-identical unknown control directions are discussed for different agents. The application of the event-triggered mechanism can effectively decrease the update frequency of the controller, and unknown nonlinear dynamics are solved by using fuzzy logic systems. Under the action of the designed distributed controller, all signals of this stochastic multi-agent systems can reach semi-globally uniformly ultimately bounded (SGUUB) in mean square. Furthermore, Zeno behavior can be ruled out by the existence of positive inter-event intervals. Finally, a simulation example is presented to verify the feasibility of the algorithm.

     

网络攻击下多智能体系统动态事件触发一致性

研究网络攻击下一般线性多智能体系统的动态事件触发一致性问题.考虑多智能体系统在受到网络攻击后,被攻击节点的状态会改变,导致与其相应的连接无法工作,设计修复策略恢复被攻击节点及其相应的连接,给出网络攻击下分布式事件触发控制协议.在静态事件触发机制基础上,通过引入动态阈值参数,提出动态事件触发机制.进一步,利用图论、线性矩阵不等式和李雅普诺夫函数方法,给出网络攻击下实现多智能体系统一致性的充分条件,并证明在所提出的动态事件触发条件下,能够有效避免芝诺行为.最后,通过仿真例子来验证理论结果的有效性.