复杂分数阶多自主体系统的运动一致性

复杂环境中,许多自然现象的动力学特性不能应用整数阶方程描述,而只能用分数阶（非整数阶）动力学的智能个体合作行为来解释. 本文假设多自主体 系统存在个体差异,采用不同的分数阶动力学特性组成复杂分数混合阶微分方程. 应用分数阶系统的Laplace变换和频域理论,研究了有向网络拓扑下,时延分数混合阶多自主体系统的运动一致性. 由于整数阶系统是分数阶系统的特殊情况,本文的结论可以推广到整数阶与分数阶混合的多自主体系统中. 最后,应用仿真实例对本文结论进行了验证.     

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.     

Finite interval tracking algorithm for nonlinear multi-agent systems with communication delays

We propose an iterative learning control (ILC) tracking strategy to solve the tracking problem of multi-agent systems with nonlinear dynamics and time-varying communication delays. The distributed tracking strategy, in which each tracking agent only utilises its own and neighbours’ information, enables the tracking agents successfully track a maneuvering target in a finite time interval although with presence of time delays. Compared with the existing related work, the quantitative relationship between the boundary of tracking errors and the estimation of time delays is derived. Furthermore, in many practical control problems, identical initialisation condition may not be satisfied, which is called initial-shift problem. Hence, a forgetting factor is introduced to deal with that problem. It is proved that the presented results are effective via conducting numerical examples.     

基于神经网络的高阶随机非线性系统的状态反馈控制

基于神经网络(NN)研究了一类含有未知非线性项的高阶随机不确定系统的自适应状态反馈控制问题. 通过引入径向基函数神经网络(RBF NN) 逼近方法, 运用 backstepping 技术以及选择合适的 Lyapunov 函数, 我们构造了一个自适应状态反馈控制器使得闭环系统是半全局一致最终有界的. 仿真例子验证了设计方法的有效性.     

Adaptive containment control of nonlinear multi-agent systems with non-identical agents

This paper addresses the containment control problem for a group of non-identical agents, where the dynamics of agents are supposed to be nonlinear with unknown parameters and parameterised by some functions. In controller design approach for each follower, adaptive control and Lyapunov theory are utilised as the main control strategies to guarantee the convergence of all non-identical followers to the dynamic convex hull formed by the leaders. The design of distributed adaptive controllers is based on the exchange of neighbourhood errors among the agents. For analysis of containment control problem, a new formulation has been developed using M-matrices. The validity of theoretical results are demonstrated through an example.     

基于一类连续非线性函数的多智能体系统有限时间一致性

针对存在时滞的多智能体系统,提出了基于一类连续非线性函数的有限时间一致性算法.利用Lyapunov有限时间稳定性理论和矩阵理论,给出了这类算法使得系统能够在有限时间内达到一致的充分条件,进而给出了一个满足条件的有限时间一致性算法,并对该算法的收敛性进行分析,得到了系统的收敛时间.数值仿真验证了所提出算法的有效性.     

Event-triggered distributed containment control of heterogeneous linear multi-agent systems by an output regulation approach

In this paper, the event-triggered distributed containment control of heterogeneous linear multi-agent systems in the output regulation framework is studied. The leaders are treated as exosystems and the containment control problem will be converted into an output regulation problem. An event-triggered protocol is then designed for each follower by the output information of neighbours. It is proved that the followers can asymptotically converge to the dynamic convex hull spanned by multiple leaders under the designed protocol and triggered strategy. Furthermore, it is shown that the proposed protocol and triggered condition can exclude Zeno behaviour, so the feasibility of the control strategy is verified. Finally, a numerical simulation is given to illustrate the effectiveness of the proposed protocol.     

带强连通分支的多智能体系统可控包含控制

研究有强连通子图拓扑结构的有向多智能体系统领导者选择及可控包含控制问题.根据网络拓扑结构,智能体被分为两类:单元智能体和一般智能体.首先设计强连通子图中个体组成的单元智能体的一致性协议实现各个单元的一致;后由单元智能体和一般智能体构成新的拓扑结构,结合复杂网络可控性理论与二分图最大匹配算法确定满足网络可控的最少领导者集合,并为所有智能个体设计相应的控制协议,驱使跟随者渐近收敛到多个领导者组成的动态凸包中,从而实现网络的可控包含控制.仿真结果验证了理论分析的正确性.     

A separation theorem for the stochastic sampled-data LQG problem†

This paper considers the control of a continuous linear plant disturbed by white plant noise when the control is constrained to be a piecewise constant function of time: i.e. a stochastic sampled-data system. The cost function is the integral of quadratic error terms in the state and control, thus penalizing errors at every instant of time while the plant noise disturbs the system continuously. The problem is solved by reducing the constrained continuous problem to an unconstrained discrete one. It is shown that the separation principle for estimation and control still holds for this problem when the plant disturbance and measurement noise are Gaussian.     

具有通信时延的二阶多智能体系统有限时间一致性跟踪控制

针对具有通信时延的二阶多智能体系统的有限时间一致性控制问题,分别研究了具有固定拓扑和切换拓扑网络结构情形下的二阶多智能体系统的有限时间一致性。为使多智能体系统能在有限时间内可以达到一致,引入一致性控制增益矩阵并设计了相应的基于相对位置和相对速度的时延状态误差有限时间一致性控制算法,利用系统模型转换,泛函微分方程稳定性理论和有限时间Lyapunov稳定性定理得到了使系统在有限时间内达到一致跟踪的最大时延上界值。最后,仿真实验结果验证了所得理论的正确性和有效性。     

具有多个通信时延的多智能体系统分布式H∞一致性控制

考虑具有多个时变时延和外部噪声干扰的一阶多智能体系统H∞一致性问题,分别讨论了固定和变化网络拓扑情形.首先,对原来的系统作一个模型变换使之转化为一个降阶的子系统;其次,根据得到的降阶系统,通过构建适当的Lyapunov函数,得到了所有智能体状态达到一致并满足期望的H∞性能的充分条件.仿真结果验证了所提出的一致性协议的正确性和有效性.     

二阶多智能体系统包含控制的时滞范围优化

研究具有未知时滞的二阶多智能体系统的鲁棒包含控制问题,考虑智能体之间同时具有通信延时和自延时,分别在无向拓扑和有向拓扑通信下,获得多智能体系统保持鲁棒包含控制所能允许的最大时滞范围.借助函数的凸分析和非线性规划方法解析地获得了无向图下包含控制所允许的最大时滞范围.对于有向图,通过遗传算法求解非光滑的优化问题获得最大时滞范围的数值解,同时结果可退化为领导-跟随控制所能获得的最大时滞范围.最后,通过仿真例子验证所提出理论和算法的有效性.