RELAXED CONDITIONS FOR CONSENSUS IN MULTI-AGENT COORDINATION

This paper proposes relaxed sufficient conditions for the consensus of multi-agent systems by the averaging protocols with time-varying system topology. Bidirectional information exchange between neighboring agents is considered and both the discrete-time and continuous-time consensus protocols are studied. It is shown that the consensus is reached if there exists an unbounded time sequence such that two agents who own the maximum and minimum states at each time instant in the sequence will be jointly connected at some future time. Further, this result is applied to the original nonlinear Vicsek model, and a sufficient condition for the heading consensus of the group with restricted initial conditions is obtained.     

FLOCKING OF MULTI-AGENT DYNAMIC SYSTEMS WITH GUARANTEED GROUP CONNECTIVITY*

This paper investigates distributed flocking problem where the information exchange among agents is modeled by the communication topology changing with time. Previous research on this problem establishes group stabilization by assuming that the dynamic topology is connected all the time, which however cannot be guaranteed by most proposed distributed control laws. In this paper, a distributed algorithm to distill a necessary subgraph of the initial communication topology is presented. This subgraph covers all the vertices of the communication topology and is proved to be connected as long as the initial communication topology is connected. A distributed control law is then designed to pursue the flocking motion while preserving all the edges in this subgraph. In this way, connectivity can be preserved all the time, and flocking problem is thus solved only provided the initial communication topology of multi-agent system is connected.     

基于智能体的多移动机器人群集编队控制系统

群是一种普遍存在的自然现象,群集编队控制是模拟自然界中生物聚合运动的新型分散式控制方法。提出了一种基于智能体的有leader的群集控制算法。在此基础上,引入“虚拟力”的概念,运用动力学原理设计了由智能体到移动机器人的控制转化方法,并实现了一个实用化的多移动机器人群集控制系统。移动机器人群编队实验验证了该方法的有效性。     

Soft-control for collective opinion of weighted DeGroot model

The DeGroot model is a classic model to study consensus of opinion in a group of individuals(agents). Consensus can be achieved under some circumstances. But when the group reach consensus with a convergent opinion value which is not what we expect, how can we intervene the system and change the convergent value? In this paper a mechanism named soft control is first introduced in opinion dynamics to guide the group's opinion when the population are given and evolution rules are not allowed to change. According to the idea of soft control, one or several special agents,called shills, are added and connected to one or several normal agents in the original group. Shills act and are treated as normal agents. The authors prove that the change of convergent opinion value is decided by the initial opinion and influential value of the shill, as well as how the shill connects to normal agents. An interesting and counterintuitive phenomenon is discovered: Adding a shill with an initial opinion value which is smaller(or larger) than the original convergent opinion value dose not necessarily decrease(or increase) the convergent opinion value under some conditions. These conditions are given through mathematical analysis and they are verified by the numerical tests. The authors also find out that the convergence speed of the system varies when a shill is connected to different normal agents. Our simulations show that it is positively related to the degree of the connected normal agent in scale-free networks.     

Stability radius of non-smooth pritchard-salamon systems and the algebraic Riccati equation

The authors discuss the stability radius of the non-smooth Pritchard-Salamon systems under structured perturbations. A formula for the stability radius in terms of the norm of a certain input-output operator is obtained. Furthermore, the relationship between stability radius and the solvability of some type of algebraic Riccati equations is given. This research is supported by the National Natural Science Foundation of China under Grant Nos. 10626057 and 10571165.     

Consensus of Flocks under M-Nearest-Neighbor Rules

This paper investigates a class of flocks with an M-nearest-neighbor rule,where each agent’s neighbors are determined according to M nearest agents with M being a given integer,rather than all the agents within a fixed metric distance as in the well-known Vicsek’s model.Such a neighbor rule has been validated by biologists through experiments and the authors will prove that,similar to the Vicsek’s model,such a new neighbor rule can also achieve consensus under some conditions imposed only on the system’s speed and the number M,n,without resorting to any priori connectivity assumptions on the trajectory of the system.In particular,the authors will prove that if the number M is proportional to the population size n,then for any speed v,the system will achieve consensus with large probability if the population size is large enough.     

带有初态学习的指数变增益迭代学习控制

针对一类非线性时变系统在有限时间区间上的轨迹跟踪问题,提出一种新的迭代学习控制算法,该算法对系统的控制输入和初始状态同时采用闭环指数变增益迭代学习律。基于算子理论,对具有任意初始状态的系统,在该迭代学习律作用下的收敛性进行严格证明,同时给出该迭代学习算法收敛的谱半径形式的充分条件。该算法与固定增益的迭代学习控制相比较,不仅加快了收敛速度,而且还解决了指数变增益迭代学习控制要求初始状态严格重复的问题。仿真结果表明了该算法的有效性。     

The Dynamics of Two-State Public Opinion Propagation On Signed Networks

The formation of public opinion on the network is a hot issue in the field of complex network research, and some classical dynamic models are used to solve this problem. The signed network is a particular form of the complex network, which can adequately describe the amicable and hostile relationships in complex real-world systems. However, the methods for studying the dynamic process of public opinion propagation on signed networks still require to be further discussed. In this paper, the authors pay attention to the influence of negative edges in order to design a two-state public opinion propagation mechanism suitable for signed networks. The authors first set the interaction rules between nodes and the transition rules of node states and then apply the model to synthetic and real-world signed networks. The simulation results show that there is a critical value of the negative edge ratio.When the negative edge ratio exceeds this critical value, the evolutionary result of public opinion will change from a consistent state to a split state. This conclusion is also consistent with the distribution result of opinions within communities in the signed network. Besides, the research on the network structural balance shows that the model makes the network evolve in a more balanced direction.     

Discovering non-terminating inputs for multi-path polynomial programs

This paper investigates the termination problems of multi-path polynomial programs （MPPs） with equational loop guards. To establish sufficient conditions for termination and nontermination simultaneously, the authors propose the notion of strong/weak non-termination which under/over- approximates non-termination. Based on polynomial ideal theory, the authors show that the set of all strong non-terminating inputs （SNTI） and weak non-terminating inputs （WNTI） both correspond to tile real varieties of certain polynomial ideals. Furthermore, the authors prove that the variety of SNTI is computable, and under some sufficient conditions the variety of WNTI is also computable. Then by checking the computed SNTI and WNTI varieties in parallel, termination properties of a consid- ered MPP can be asserted. As a consequence, the authors establish a new framework for termination analysis of MPPs.     

Maximum likelihood estimator of the parameter for a continuous one-parameter exponential family under the optimal ranked set sampling

This paper studies a maximum likelihood estimator (MLE) of the parameter for a continuous one-parameter exponential family under ranked set sampling (RSS). The authors first find the optimal RSS according to the character of the family, viz, arrange the RSS based on quasi complete and sufficient statistic of independent and identically distributed (iid) samples. Then under this RSS, some sufficient conditions for the existence and uniqueness of the MLE, which are easily used in practice, are obtained. Using these conditions, the existence and uniqueness of the MLEs of the parameters for some usual distributions in this family are proved. Numerical simulations for these distributions fully support the result from the above two step optimizations of the sampling and the estimation method.     

Approximate conditional likelihood for generalized linear models with general missing data mechanism

The generalized linear model is an indispensable tool for analyzing non-Gaussian response data, with both canonical and non-canonical link functions comprehensively used. When missing values are present, many existing methods in the literature heavily depend on an unverifiable assumption of the missing data mechanism, and they fail when the assumption is violated. This paper proposes a missing data mechanism that is as generally applicable as possible, which includes both ignorable and nonignorable missing data cases, as well as both scenarios of missing values in response and covariate. Under this general missing data mechanism, the authors adopt an approximate conditional likelihood method to estimate unknown parameters. The authors rigorously establish the regularity conditions under which the unknown parameters are identifiable under the approximate conditional likelihood approach. For parameters that are identifiable, the authors prove the asymptotic normality of the estimators obtained by maximizing the approximate conditional likelihood. Some simulation studies are conducted to evaluate finite sample performance of the proposed estimators as well as estimators from some existing methods. Finally, the authors present a biomarker analysis in prostate cancer study to illustrate the proposed method.     

Output consensus for heterogeneous nonlinear multi-agent systems based on T-S fuzzy model

In this paper, the output consensus problem of general heterogeneous nonlinear multi-agent systems subject to different disturbances is considered. A kind of Takagi-Sukeno fuzzy modeling method is used to describe the nonlinear agents’ dynamics. Based on the model, a distributed fuzzy observer and controller are designed based on parallel distributed compensation scheme and internal reference models such that the heterogeneous nonlinear multi-agent systems can achieve output consensus. Then a necessary and sufficient condition is presented for the output consensus problem. And it is shown that the consensus trajectory of the global fuzzy model is determined by the network topology and the initial states of the internal reference models. Finally, some simulations are given to illustrate and verify the effectiveness of the proposed scheme.     

基于动态拓扑有领航者的智能群体群集运动控制

对具有二次积分动态的智能群体跟随领航者实现群集运动编队,提出了一个分散控制方法对智能群体进行分散控制。基于动态时变有领航者的网络拓扑,用图论模型表示智能体之间的相互作用及通信关系,运用推广的Lyapunov理论、微分包含及非平滑分析进行了稳定性分析,并得到所有智能体速度方向收敛到同一方向并与领航者保持一致;所有智能体速度大小收敛并与领航者相同;互连的智能体之间没有碰撞发生;所有智能体的人工势场函数被最小化等重要结论。给出了一个仿真实例,验证了该方法的有效性。     

Generalized F-test for high dimensional regression coefficients of partially linear models

This paper proposes a test procedure for testing the regression coefficients in high dimensional partially linear models based on the F-statistic. In the partially linear model, the authors first estimate the unknown nonlinear component by some nonparametric methods and then generalize the F-statistic to test the regression coefficients under some regular conditions. During this procedure, the estimation of the nonlinear component brings much challenge to explore the properties of generalized F-test. The authors obtain some asymptotic properties of the generalized F-test in more general cases,including the asymptotic normality and the power of this test with p/n ∈(0, 1) without normality assumption. The asymptotic result is general and by adding some constraint conditions we can obtain the similar conclusions in high dimensional linear models. Through simulation studies, the authors demonstrate good finite-sample performance of the proposed test in comparison with the theoretical results. The practical utility of our method is illustrated by a real data example.     

Consensus control design for multi-agent systems using relative output feedback

This paper studies the consensus problem of multi-agent systems in which all agents are modeled by a general linear system. The authors consider the case where only the relative output feedback between the neighboring agents can be measured. To solve the consensus problem, the authors first construct a static relative output feedback control under some mild constraints on the system model. Then the authors use an observer based approach to design a dynamic relative output feedback control. If the adjacent graph of the system is undirected and connected or directed with a spanning tree, with the proposed control laws, the consensus can be achieved. The authors note that with the observer based approach, some information exchange between the agents is needed unless the associated adjacent graph is completely connected.     

Consensus of Linear Multi-Agent Systems with Persistent Disturbances via Distributed Output Feedback

This paper addresses the consensus problem of general linear multi-agent systems with persistent disturbances by distributed output feedback. Suppose that states of agents can not be obtained directly. Several estimators are designed to observe states of agents and the unknown disturbances.A protocol is proposed to drive all agents achieve consensus. Based on the method of model transformation and the property of permutation matrix, sufficient conditions for consensus are obtained in terms of linear matrix inequalities. Finally, simulations are given to show the effectiveness of presented results.     

On Robust Stability of a Class of Uncertain Nonlinear Systems with Time—Varying Delay

The problem of robust stability of a class of uncertain nonlinear dynamical systems with time-delay is considered. Based on the assumption that the nominal system is stable, some sufficient conditions on robust stability of uncertain nonlinear dynamical systems with time-delay are derived. Some analytical methods and a type of Lyapunov functional are used to investigate such sufficient conditions. The results obtained in this paper are applicable to perturbed time-delay systems with unbounded time-varying delay. Some previous results are improved and a numerical example is given to demonstrate the validity of our results.     

任意初始状态下非正则系统的迭代学习控制设计

迭代学习控制已广泛应用于各种机器人控制系统,但目前的方法大多数都假设系统具有零初始误差。在实际工程应用中,迭代学习的初始状态往往会发生漂移,现有的学习算法不能正确地使用。针对具有非零初始误差的非正则线性离散系统,研究了其迭代学习算法,提出了两种新型的初始状态的学习方法,利用2 D系统理论,对迭代学习进行了2 D分析,以保证所提出算法的稳定性。由于不需要假设系统初始误差为零,该算法更符合工程实际,仿真验证了算法的有效性。     

New results about the relationship between optimally weighted least squares estimate and linear minimum variance estimate

The optimally weighted least squares estimate and the linear minimum variance estimate are two of the most popular estimation methods for a linear model. In this paper, the authors make a comprehensive discussion about the relationship between the two estimates. Firstly, the authors consider the classical linear model in which the coefficient matrix of the linear model is deterministic, and the necessary and sufficient condition for equivalence of the two estimates is derived. Moreover, under certain conditions on variance matrix invertibility, the two estimates can be identical provided that they use the same a priori information of the parameter being estimated. Secondly, the authors consider the linear model with random coefficient matrix which is called the extended linear model; under certain conditions on variance matrix invertibility, it is proved that the former outperforms the latter when using the same a priori information of the parameter. This research is supported in part by the National Natural Science Foundation of China under Grant Nos. 60232010, 60574032, and the Project 863 under Grant No. 2006AA12A104.     

交通信息发布条件下确定性均衡和随机均衡的存在性分析与比较

在路径费用为二次分段函数的假设条件下讨论了确定性均衡解和有信息发布时的随机均衡解存在的充要条件,并对相应条件下交通信息的有效性进行了评价,得到了一系列较为实用的解析性结论,最后给出了若干算例分析。