基于马尔科夫拓扑切换和随机通信干扰的连续时间多自主体系统的趋同控制

研究了基于不可靠通信网络的连续时间多自主体系统的趋同控制.自主体间的通信信道受高斯噪声干扰;不可靠通信因素导致的网络拓扑随机切换由马氏链刻画.为克服随机噪声和马尔科夫拓扑切换的影响,设计了随机逼近型趋同协议;基于马氏跳参数随机微分方程稳定性理论、代数图理论、连续鞅和马氏链理论,证明了多自主体系统实现渐近无偏均方平均趋同...     

非平衡拓扑和随机干扰情形下多自主体系统的趋同条件

研究了具有一般有向通信拓扑和高斯通信噪声的多自主体系统的趋同条件.这里所研究的有向拓扑不仅包含有向平衡图,而且包含非平衡图,后者是本文的重点.我们利用马氏链的结果得到了一个网络节点的互通类;通过对噪声影响的细化,给出了不同噪声情形下系统趋同条件:(1)对互通类的自主体获取信息受到噪声干扰情形,给出了系统均方趋同的充要条件,并证明该条件也保证以概率1 趋同;(2)对互通类的自主体获取信息未受到噪声干扰但其余自主体获取信息受到干扰情形,给出了系统均方趋同的充分条件,并证明该条件在一定意义下也是必要的;(3)对整个系统无噪声情形,给出了系统趋同的充要条件.     

多自主体系统的分析与干预

多自主体系统集体行为的研究可以分为三类:分析,设计和干预.针对经典的群集模型-Vicsek模型及其相关模型,介绍了系统控制重点实验室近年来取得的研究成果和进展,主要包括概率框架下Vicsek模型的同步分析,以及针对干预问题提出的软控制等方法在Vicsek模型同步问题和多人博弈系统合作问题中的应用.     

具有随机不确定通讯连接和马氏切换拓扑的多自主体系统的鲁棒H∞领导跟踪一致性研究

文章研究了马氏切换拓扑下多自主体系统的鲁棒H∞领导跟踪一致性问题.由于通讯环境中难以预知的变化,自主体之间的通讯连接可能具有随机的不确定成分,文章用伯努利分布序列来描述这种随机不确定性.同时,在很多实际系统中,想精准获得马氏跳变过程的转移率矩阵中的元素是不容易的,或者获取成本很高,因此文章中马氏切换拓扑的转移率是假定为...     

多四旋翼无人机分布式固定时间自适应编队控制

针对具有外部扰动和参数不确定性的多四旋翼无人机,提出了基于指令滤波反步方法的分布式固定时间自适应编队控制算法.通过引入固定时间指令滤波及构建非光滑误差补偿机制,有效地避免了“复杂性爆炸”问题并在固定时间内移除了滤波误差的影响.此外,通过设计分段函数,巧妙地解决了分布式控制器中存在的奇异性问题.利用固定时间稳定性理论,严格证明了闭环系统是实际固定时间稳定的,且闭环系统中所有信号有界,同时编队跟踪误差在固定时间内收敛到原点附近充分小的邻域内.最后,仿真算例验证了所提出的分布式固定时间控制策略的有效性.     

基于actor-critic算法的分数阶多自主体系统最优主-从一致性控制

研究了分数阶多自主体系统的最优主-从一致性问题.在考虑控制器周期间歇的前提下,将分数阶微分的一阶近似逼近式、事件触发机制和强化学习中的actor-critic算法有机整合,设计了基于周期间歇事件触发策略的强化学习算法结构.最后,通过数值仿真实验证明了该算法的可行性和有效性.     

函数空间多体挠性结构系统动力学、稳定性与控制的研究

利用现代数学方法,在函数空间中研究了一类无穷维系统动力学、稳定性与控制问题.首先提出并建立了具有阻尼、陀螺部件和约束阻尼的多拓扑结构多挠体分布参数系统动力学控制模型;其次给出并论证了多体挠性结构特征、系统分析结果--可控可观性充要条件、稳定性理论和系统的渐近性质.研究的结果扩充和发展了本领域关于多挠体系统动力学与控制的理论成果,具有重要的工程意义.     

一类不确定非线性时滞系统的模糊自适应控制

针对一类不确定上界未知的非线性时滞系统,基于松散稳定性条件,讨论了系统的模糊自适应控制问题 .通过在Lyapunov泛函中引入参数,得到带调节因子的时滞相关稳定性条件.设计出基于观测器的自适应模糊控制器,观测增益矩阵和反馈增益矩阵可以通过求解线性矩阵不等式得到 .当调节因子取不同值时,观测增益矩阵和反馈增益矩阵也是不同的,因此,闭环系统的动态性能可以通过选取合适的调节因子来优化.最后通过一个实例验证了所给结论的有效性.     

离散时间大种群随机多智能体系统的线性二次分散动态博弈

研究具有耦合二次型随机性能指标的离散时间大种群随机多智能体系统的分散博弈问题.系统所受的噪声干扰为条件二阶矩有界的鞅差序列,比以往研究所考虑的高斯白噪声情形更具有广泛性.采用状态聚集方法构造了对种群状态平均的估计,基于Nash必然等价原理设计了分散控制律,并利用概率极限理论分析了闭环系统的稳定性和最优性.主要结果包括(1)证明了对种群状态的平均的估计在某种范数意义下的强一致性,即种群状态的平均与其估计值之间的误差在该范数意义下将随系统个体数N的增加几乎必然收敛于0;(2)证明了闭环系统的几乎必然一致稳定性,即系统的稳定性与种群个体数N无关;(3)证明了所设计的分散控制律是几乎必然渐近Nash均衡策略.     

具有外部干扰的非线性多智能体系统的编队控制

多智能体系统编队控制因广泛应用于军事,航天,生物学等领域,成为国内外学者的关注热点.在实际应用中,当系统受到环境噪声等外部干扰时,利用领航者-跟随者的相对状态信息构造控制器无法形成预期队形.为解决这个问题,文章针对一类带有外部干扰的非线性多智能体系统,研究了领航-跟随编队控制问题.首先设计干扰观测器补偿外部干扰.其次利用自适应方法,给出了完全分布式的控制协议.再次选取适当的参数,证明了该分布式控制协议能实现系统的编队控制.最后通过仿真算例,验证了协议的有效性.     

Distributed adaptive switching consensus control of heterogeneous multi-agent systems with switched leader dynamics

In this paper, the leader-following distributed consensus control problem is addressed for general linear multi-agent systems with heterogeneous uncertain agent dynamics and switched leader dynamics. Different from most existing results with a single linear time-invariant (LTI) leader dynamics, the leader dynamics under consideration is composed by a family of LTI models and a switching logic governing the switches among them, which is capable of generating more diverse and sophisticated reference signals to accommodate more complicated consensus control design tasks. A novel distributed adaptive switching consensus protocol is developed by incorporating the model reference adaptive control mechanism and arbitrary switching control technique, which can be synthesized by following a two-layer hierarchical design scheme. A numerical example has been used to demonstrate the effectiveness of the proposed approach.     

Iterative learning consensus control with initial state learning for fractional order distributed parameter models multi-agent systems

This paper considers the consensus control problem of multi-agent systems (MAS) with distributed parameter models. Based on the framework of network topologies, a second-order PI-type iterative learning control (ILC) protocol with initial state learning is proposed by using the nearest neighbor knowledge. A discrete system for proposed ILC is established, and the consensus control problem is then converted to a stability problem for such a discrete system. Furthermore, by using generalized Gronwall inequality, a sufficient condition for the convergence of the consensus errors between any two agents is obtained. Finally, the validity of the proposed method is verified by two numerical examples.     

Adaptive control of linear stochastic evolution systems

An adaptive control problem for some linear stochastic evolution systems in Hilbert spaces is formulated and solved in this paper. The solution includes showing the strong consistency of a family of least squares estimates of the unknown parameters and the convergence of the average quadratic costs with a control based on these estimates to the optimal average cost. The unknown parameters in the model appear affinely in the infinitesimal generator of the C ₀ semigroup that defines the evolution system. A recursive equation is given for a family of least squares estimates and the bounded linear operator solution of the stationary Riccati equation is shown to be a continuous function of the unknown parameters in the uniform operator topology     

Consensus of heterogeneous multi-agent systems with linear and nonlinear dynamics

In this paper, we perform an in-depth study about the consensus problem of heterogeneous multi-agent systems with linear and nonlinear dynamics.Specifically, this system is composed of two classes of agents respectively described by linear and nonlinear dynamics. By the aid of the adaptive method and Lyapunov stability theory, the mean consensus problem is realized in the framework of first-order case and second-order case under undirected and connected networks.Still, an meaningful example is provided to verify the effectiveness of the gained theoretical results. Our study is expected to establish a more realistic model and provide a better understanding of consensus problem in the multi-agent system.     

Robust fixed-time consensus protocols for multi-agent systems with nonlinear state measurements

This paper solves the robust fixed-time consensus problem for multi-agent systems with nonlinear state measurements. Sufficient conditions are established for the proposed protocol to reach fixed-time consensus under time-varying undirected and fixed directed topology with the aid of Lyapunov functions. It is proved that the finite settling time of the presented protocol for robust consensus is uniformly bounded for any initial condition, which makes it possible for people to design and estimate the convergence time off-line. Numerical simulations are preformed to show the effectiveness of our proposed protocol.     

On the ergodic and the adaptive control of stochastic differential delay systems

Some problems of ergodic control and adaptive control are formulated and solved for stochastic differential delay systems. The existence and the uniqueness of invariant measures that are solutions of the stochastic functional differential equations for these systems are verified. For an ergodic cost criterion, almost optimal controls are constructed. For an unknown system, the invariant measures and the optimal ergodic costs are shown to be continuous functions of the unknown parameters. Almost self-optimizing adaptive controls are feasibly constructed by an approximate certainty equivalence principle.This research was partially supported by NSF Grants ECS-91-02714 and ECS91-13029.     

Pinning consensus control for switched multi-agent systems: A switched adaptive dynamic programming method

Stability is fundamental to ensure the operation of control system, but optimality is the ultimate goal to achieve the maximum performance. This paper investigates an event-triggered pinning optimal consensus control for switched multi-agent system (SMAS) via a switched adaptive dynamic programming (ADP) method. The technical contribution mainly lies in two aspects. On the one hand, in order to optimize the control performance and ensure the consensus, the switched local value function (SLVF) and the minimum-error switching law are constructed. Based on SLVF, an algorithm of switched ADP policy iteration is proposed, and its convergence and optimality are proved. On the other hand, considering that it is impractical to install a controller for each agent in reality, a pinning strategy is developed to guide the setting of the ADP controller, which can reduce the waste of control resources. A new condition is constructed to determine the minimum number of controlled vertices of the SMAS. Lastly, a numerical example is given to verify the effectiveness of the proposed method.     

Leader-following exponential consensus of general linear multi-agent systems via event-triggered control with combinational measurements

In this paper, the leader-following exponential consensus problem of general linear multi-agent systems via event-triggered control is considered. By using the combinational measurements, two classes of event triggers are designed, one depends on continuous communications between the agents, the other avoids continuous communications. For such two classes of event triggers, the exponential consensus as well as the convergence rates of the controlled multi-agent systems are studied, respectively, by employing the M-matrix theory, algebraic graph theory and the Lyapunov method.     

New approach to control and filtering of mechanical systems by using the estimates of their Lagrangians

When a mechanical system is defined by its Lagrangian, some control problems can be solved by using directly the latter, instead of the dynamical equations themselves; this is based upon the property that the dynamics is continuous with respect to the Lagrangian. After stating the main lemma which supports the approach, we consider applications to active mechanical systems, that is to say, with time-varying structural parameters, to tracking control via external applied forces, and to state estimation problems for which we propose a new variational principle.This research was supported by the National Research Council of Canada.     

Distributed impulsive control consensus for a class of unknown nonlinear multi-agent systems based on event-triggered scheme

In this study, we are concerned with the impulsive consensus control problem for a class of nonlinear multi-agent systems (MASs) which have unknown dynamics and directed communication topology. The neural networks (NNs) method is the first utilized to construct distributed event-triggered impulsive consensus protocol. In contrast to the existing impulsive consensus protocol, the consensus protocol proposed in this paper does not need the dynamics of agents, which enhances the system robustness, and realizes distributed event-triggered communication between agents, which can reduce unnecessary consumption of communication resources. Sufficient conditions are derived to ensure the consensus of the controlled MASs and the exclusion of Zeno-behavior. Finally, simulation examples are presented to illustrate the effectiveness of the proposed control protocol.