Consensus seeking in multi-agent systems via hybrid protocols with impulse delays

This paper studies the consensus problem of multi-agent systems with both fixed and switching topologies. A hybrid consensus protocol is proposed to take into consideration of continuous-time communications among agents and delayed instant information exchanges on a sequence of discrete times. Based on the proposed algorithms, the multi-agent systems with the hybrid consensus protocols are described in the form of impulsive systems or impulsive switching systems. By employing results from matrix theory and algebraic graph theory, some sufficient conditions for the consensus of multi-agent systems with fixed and switching topologies are established, respectively. Our results show that, for small impulse delays, the hybrid consensus protocols can solve the consensus problem if the union of continuous-time and impulsive-time interaction digraphs contains a spanning tree frequently enough. Simulations are provided to demonstrate the effectiveness of the proposed consensus protocols.     

Sampled-data control of uncertain switched neutral nonlinear systems under asynchronous switching

The robust exponential stabilization for a class of the uncertain switched neutral nonlinear systems with time-varying delays based on the sampled-data control is investigated in this paper. The closed-loop system with sampled-data control is modeled as a continuous time system with a time-varying piecewise continuous control input delay. Considering the relationship between the sampling period and the dwell time of two switching instants, sampling interval with no switching and sampling interval with one switching are discussed, respectively. By Wirtinger-based inequality, Wirtinger-based double integral inequality, and free-weighting matrix technique, some delay-dependent sufficient conditions are given to guarantee the exponential stability of uncertain switched neutral nonlinear systems under asynchronous switching. In addition, sampled-data controllers can also be designed by special operations of matrices. Finally, two numerical examples are used to show the effectiveness of the approach proposed in this paper.     

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.     

Neural network hybrid adaptive control for nonlinear uncertain impulsive dynamical systems

A neural network hybrid adaptive control framework for nonlinear uncertain hybrid dynamical systems is developed. The proposed hybrid adaptive control framework is Lyapunov-based and guarantees partial asymptotic stability of the closed-loop hybrid system; that is, asymptotic stability with respect to part of the closed-loop system states associated with the hybrid plant states. A numerical example is provided to demonstrate the efficacy of the proposed hybrid adaptive stabilization approach.     

Flocking of mobile intelligent agents on fuzzy system with optimal theories

A dynamical model is presented for autonomous mobile intelligent agents. Based on the local information of the swarm, a fuzzy logical controller (FLC) is built for the attraction/repulsion function. The flocking of the separation, cohesion and alignment are achieved by combining with the rate consensus algorithm. Based on the optimal controller theories, a performance target is used to measure the states of the system. By applying the connected network from the individual local perceived information, the aggregation of the multi-agent systems can swarm following a whole consensus in the computer simulations.     

Second-order consensus for heterogeneous multi-agent systems in the cooperation–competition network: A hybrid adaptive and pinning control approach

In this paper, a second-order consensus problem is investigated for the heterogeneous agents in the cooperation–competition network, with the parameters of the agents’ dynamics being uncertain. By introducing an exosystem, a hybrid adaptive and pinning control strategy is firstly proposed to ensure that all the agents follow a desired trajectory which is a function of the exosystem state. Several effective sufficient conditions are obtained by applying algebraic graph theory and the Barbalat lemma. Besides, the switching topologies between the competition agents are also considered. With the help of the Barbalat-like lemma, it is found that second-order consensus problem of the heterogeneous agents can be solved even when the competition sub-network is dynamic. Finally, simulation results are presented to validate the effectiveness of the theoretical analysis.     

具有部分状态信息的二阶多智能体系统的一致性

研究二阶连续多智能体系统的一致性问题,其中每个智能体只能在一系列离散时刻上获得位置信息.为了关于完全状态,即位置和速度,都达到一致,设计一类协议,并建立在该协议下,一致性成立的充要条件.该条件揭示了交流拓扑、控制器增益、采样周期和保持器的更新周期之间的关系.仿真例子表明理论结果是有效的.     

A model of influence based on aggregation functions

The paper concerns a dynamic model of influence in which agents make a yes–no decision. Each agent has an initial opinion which he may change during different phases of interaction, due to mutual influence among agents. We investigate a model of influence based on aggregation functions. Each agent modifies his opinion independently of the others, by aggregating the current opinion of all agents. Our framework covers numerous existing models of opinion formation, since we allow for arbitrary aggregation functions. We provide a general analysis of convergence in the aggregation model and find all terminal classes and states. We show that possible terminal classes to which the process of influence may converge are terminal states (the consensus states and nontrivial states), cyclic terminal classes, and unions of Boolean lattices (called regular terminal classes). An agent is influential for another agent if the opinion of the first one matters for the latter. A generalization of influential agent to an irreducible coalition whose opinion matters for an agent is called influential coalition. The graph (hypergraph) of influence is a graphical representation of influential agents (coalitions). Based on properties of the hypergraphs of influence we obtain conditions for the existence of the different kinds of terminal classes. An important family of aggregation functions–the family of symmetric decomposable models–is discussed. Finally, based on the results of the paper, we analyze the manager network of Krackhardt.     

Nonfragile dynamic output-feedback control for positive singular systems under the switched mechanism and Round-Robin protocol

In this paper, the singular positive system with uncertain parameters and switched structure is analyzed. First of all, a nonfragile dynamic output-feedback controller with Round-Robin protocol is constructed so as to decrease the occupancy of the communication channels and overcome the phenomenon of controller gain fluctuations. Then, the regularity, causality, positivity, and robustly exponential stability of the resultant closed-loop system are discussed respectively by utilizing the method of mode dependent minimum dwell time, mode dependent ranged dwell time, and mode dependent constant dwell time. The explicit design mechanisms of the related controller parameters are simultaneously presented. Finally, two simulation examples are provided to show feasibility of the theoretical results obtained.     

Optimal Noise Rejection in Structural Analysis by Means of Generalized Sampled-Data Hold Functions

In this paper, a technique for optimal noise rejection, based on generalized sampled-data hold functions is applied to the control of civil engineering structures. The technique consists in suitably modulating the sampled outputs of the system under control by periodically varying functions in order to attenuate the effect of the disturbances on the system states to an acceptable level, by minimizing a quadratic cost function. This minimization is performed by feeding back the outputs of the system, which are assumed to be corrupted by measurement noise. Moreover, in the present paper, the robustness properties of the GSHF based optimal regulator is analyzed and guaranteed stability margins, expressed in terms of elementary cost and system matrices, are proposed for such a type of optimal regulators. The effectiveness of the method is demonstrated by various simulation results. The results of the paper can be used to assess the detrimental effect of noise on the closed-loop system and the tradeoff involved in assuring good sampled-data performance and sufficient robustness.     

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...     

Time optimal sampled-data controls for the heat equation

In this paper, we first design a time optimal control problem for the heat equation with sampled-data controls, and then use it to approximate a time optimal control problem for the heat equation with distributed controls.The study of such a time optimal sampled-data control problem is not easy, because it may have infinitely many optimal controls. We find connections among this problem, a minimal norm sampled-data control problem and a minimization problem, and obtain some properties on these problems. Based on these, we not only build up error estimates for optimal time and optimal controls between the time optimal sampled-data control problem and the time optimal distributed control problem, in terms of the sampling period, but we also prove that such estimates are optimal in some sense.     

Master–slave synchronization of continuously and intermittently coupled sampled-data chaotic oscillators

In this paper, we consider the problem of synchronizing a master–slave chaotic system in the sampled-data setting. We consider both the intermittent coupling and continuous coupling cases. We use an Euler approximation technique to discretize a continuous-time chaotic oscillator containing a continuous nonlinear function. Next, we formulate the problem of global asymptotic synchronization of the sampled-data master–slave chaotic system as equivalent to the states of a corresponding error system asymptotically converging to zero for arbitrary initial conditions. We begin by developing a pulse-based intermittent control strategy for chaos synchronization. Using the discrete-time Lyapunov stability theory and the linear matrix inequality (LMI) framework, we construct a state feedback periodic pulse control law which yields global asymptotic synchronization of the sampled-data master–slave chaotic system for arbitrary initial conditions. We obtain a continuously coupled sampled-data feedback control law as a special case of the pulse-based feedback control. Finally, we provide experimental validation of our results by implementing, on a set of microcontrollers endowed with RF communication capability, a sampled-data master–slave chaotic system based on Chua’s circuit.     

The epistemic gossip problem

In the gossip problem information (‘secrets’) must be shared among a certain number of agents using the minimum number of calls. We extend the gossip problem to arbitrary epistemic depths. For example, we may require not only that all agents know all secrets but also that all agents know that all agents know all secrets. We give optimal protocols for various versions of this epistemic gossip problem, depending on the graph of communication links, in the case of two-way communication, one-way communication and parallel communication. We show, among other things, that increasing epistemic depth from 1 (all agents know all secrets) to 2 (so that all agents know that all agents know all secrets) does not double the required number of calls but increases this number by $3∕2$ (for a complete graph). We also show that the following counter-intuitive result generalises to the epistemic gossip problem: asymptotically the same number of calls are required whether calls are two-way or one-way.     

New differentiated consensus problem with topology cost constraints

A new differentiated consensus problem is studied. The problem is, given a system with multiple classes, consensus is targeted for each class and the consensus values can be different among the classes. Specifically, differentiated consensus is studied in a distributed stochastic network of nodes (or agents), where tasks assigned with different priorities are serviced. The network is assumed to have a switching topology and involves noises, delays in measurements, and topology cost constraints. The goal is to reach a balanced load (i.e., consensus) across the network and, at the same time, to satisfy the topology cost constraint, both for each priority class. A new control protocol is proposed, with which the network resources are allocated in a randomized way with a probability assigned to each priority class. It is shown that the control protocol meets the topology cost constraint and can be used to reach an approximate consensus for each of the priority classes in the network.     

Cucker–Smale flocking under rooted leadership and time-varying heterogeneous delays

In this paper, a Cucker–Smale model with time-varying heterogeneous delays in the communication process is investigated, where the delay on each communication link is time-varying and independent of other communication links. A general update rule based on the distance between agents is used to determine the edge weights of the communication network. The method of constructing augmented system is used so that the system stability is transformed into a product convergence problem of time-varying sub-stochastic matrices equivalently. By analyzing this convergence problem, a sufficient condition is established to achieve flocking, which relates to the initial states, the structure of communication network and the upper bound of time delays.     

有向网络下多个体系统的整体行为

研究非时变有向通讯网络背景下一阶线性多个体动力学系统的整体行为.根据通讯网络的结构,系统可以区分为独立基本子系统和非独立基本子系统.当系统的控制规则为一类平凡的线性类型时,系统的独立基本子系统将趋于自身的一致状态,也即子系统中的每个个体趋于子系统的带权中心.独立基本子系统带权中心由子系统的系数矩阵的零特征根归一化左特征向量确定.非独立子系统中个体将趋于独立基本子系统带权中心的凸集内.当且仅当系统的独立基本子系统唯一时,系统实现一致性行为.     

一阶多智能体系统的一致性分析

研究一阶连续多智能体系统的一致性问题,其中每个智能体只能在一系列离散时刻上获得其相对邻居的状态信息,并且每个智能体的保持器的周期和采样器的周期是不同的.通过分析多智能体系统的稳定性,获得了一致性成立的充要条件,该条件揭示了交流拓扑、控制器增益、采样器的周期和保持器的周期的关系.最后,提供一个仿真例子以说明理论结果的有效性.