Bipartite Consensus of Linear Multi-Agent Systems by Distributed Event-Triggered Control

For multi-agent systems with competitive and collaborative relationships, signed graph can more intuitively express the characteristics of their interactive networks. In this paper, the bipartite consensus is investigated for multi-agent systems with structurally balanced signed graph. In order to reduce actuation burden in dynamical network environment, the event-triggering strategy is applied to bipartite consensus protocol for the multi-agent systems. The triggered condition for each agent is designed by using its own information and transmitted information of its neighbors at sampling instant and make the number of triggers of the whole systems be reduced. Based on the distributed eventtriggered control, some sufficient conditions are derived to guarantee the leaderless and leader-following bipartite consensus. Finally, some numerical examples are shown to demonstrate the effectiveness of the theoretical results.     

Consensus control for leader-following multi-agent systems with measurement noises

<正> This work is concerned with consensus control for a class of leader-following multi-agentsystems (MASs).The information that each agent received is corrupted by measurement noises.Toreduce the impact of noises on consensus,time-varying consensus gains are adopted,based on whichconsensus protocols are designed.By using the tools of stochastic analysis and algebraic graph theory,asufficient condition is obtained for the protocol to ensure strong mean square consensus under the fixedtopologies.This condition is shown to be necessary and sufficient in the noise-free case.Furthermore,by using a common Lyapunov function,the result is extended to the switching topology case.     

Event-Triggered Consensus for Discrete-Time Multi-agent Systems with Parameter Uncertainties Based on a Predictive Control Scheme

In this paper, the event-triggered consensus for linear discrete-time multi-agent systems with parameter uncertainties is investigated. The parameter uncertainty is assumed to be normbounded. An event-triggered consensus protocol based on the predictive control method is proposed to make the multi-agent system achieve consensus. And for the design of the consensus protocol, the problem of estimating the control input is transformed into the problem of estimating state differences between agents. Furthermore, the event-triggered consensus protocol proposed in this paper only demands each agent to mornitor its state to determine its event-triggered instants. A sufficient existence condition for the consensus protocol is proposed based on the linear matrix inequality. And a sufficient condition for the nonexistence of the Zeno-like behaviour is also derived. Finally, a numerical example is given to illustrate that the event-triggered consensus protocol proposed in this paper can make the multi-agent system with parameter uncertainties achieve consensus effectively.     

Projective Group Consensus of Multi-Agent Systems with Arbitrary Parameter

In this paper, the projective group consensus issue for second order multi-agent systems(MASs) in directed graphs with a dynamic leader is investigated. The proposed projective group consensus with arbitrary parameter includes traditional consensus, reverse group consensus and cluster consensus as its special cases. Novel distributed control protocols are designed to obtain projective group consensus without analyzing signed directed graph as in most current literatures on bipartite consensus problem. On the basis of Lyapunov stability property, algebraic graph and some necessary matrix theory, sufficient conditions for delay and delay-free cases are derived. Finally, simulations of nonlinear chaotic MASs are adopted to testify the theoretical results.     

基于多智能体导航的高超飞行器信息融合方法

精确导航技术是高超飞行器(hypersonic vehicle, HV)充分发挥威力的关键所在。然而,高马赫数和强机动性致使HV的导航系统误差及其观测噪声无法准确描述,制约着导航信息的精确性和实时性。为及时获取高精度导航信息,设计基于集员框架的卡尔曼滤波算法。一方面采用多智能体分布式协同探测,形成观测椭球交叉集合,提高了观测效率和测量精度;另一方面,通过设计两类噪声模型,求其与状态估值的最小均方误差,实现滤波增益的计算,提高算法对噪声的抗扰动能力,使状态估值达到均方误差最小。通过数字仿真,将设计方法应用到HV导航模型中,并与扩展卡尔曼滤波和集员滤波的状态估值进行比较,结果表明,提出算法在不同噪声影响下具有更高的估计精度。研究成果将为HV实现实时精确导航提供技术支持,并具有重要的理论意义和应用价值。     

Group consensus for multiple networked Euler-Lagrange systems with parametric uncertainties

In this paper,a group consensus problem is investigated for multiple networked agents with parametric uncertainties where all the agents are governed by the Euler-Lagrange system with uncertain parameters.In the group consensus problem,the agents asymptotically reach several different states rather than one consistent state.A novel group consensus protocol and a time-varying estimator of the uncertain parameters are proposed for each agent in order to solve the couple-group consensus problem.It is shown that the group consensus is reachable even when the system contains the uncertain parameters.Furthermore,the multi-group consensus is discussed as an extension of the couple-group consensus,and then the group consensus with switching topology is considered.Simulation results are finally provided to validate the effectiveness of the theoretical analysis.     

Leader-following consensus for discrete-time multi-agent systems with parameter uncertainties based on the event-triggered strategy

In this paper, the leader-following consensus for discrete-time multi-agent systems with parameter uncertainties is investigated based on the event-triggered strategy. And the parameter uncertainty is assumed to be norm-bounded. A consensus protocol is designed based on the event-triggered strategy to make the multi-agent systems achieve consensus without continuous communication among agents. Each agent only needs to observe its own state to determine its own triggering instants under the triggering function in this paper. In addition, a sufficient condition for the existence of the event-triggered consensus protocol is derived and presented in terms of the linear matrix inequality. Finally, a numerical example is given to illustrate to efficiency of the event-triggered consensus protocol proposed in this paper.     

基于变分推断的一般噪声自适应卡尔曼滤波

线性高斯状态空间模型中假设噪声为已知的白噪声过于苛刻。认为过程噪声与观测噪声均未知且二者的解析关系确定,假设观测噪声的均值非零且服从高斯分布,方差服从逆威沙特分布,从而构成了层次式贝叶斯模型。利用变分推断将均值与方差和系统状态一起作为随机变量进行迭代估计,在得到观测噪声的均值与方差的估计值后,利用其与过程噪声的关系进一步更新未知过程噪声的均值与方差,从而动态地得到每一时刻过程噪声与观测噪声的一、二阶统计矩信息,即使在噪声统计信息动态变化的情况下也有较满意的滤波精度。实验证明了该算法的有效性。     

基于适应性Agent图的交通系统脆性研究

针对系统脆性的研究,以复杂适应系统和图论为理论基础,提出了Agent图的概念,其中图的每个顶点被看作一个具有适应性的主体。然后将Agent图应用于交通系统脆性的研究,交通网络组成了一个赋权图,网络中各节点作为顶点;考虑到它们之间的交互作用,建立了系统主体崩溃程度的演化规则,进而对交通系统脆性行为进行仿真。     

基于贝叶斯估计噪声相关下的CKF设计

针对常规容积卡尔曼滤波(cubature Kalman filter, CKF)要求系统噪声和量测噪声必须互不相关的局限性,提出了一种带相关噪声的非线性离散系统CKF设计方法。基于贝叶斯估计准则,给出了系统噪声和量测噪声相关时CKF滤波递推公式,并采用三阶球面-相径容积规则来近似计算系统状态的后验均值和协方差。当系统噪声和量测噪声相关时,常规CKF不适用,本文设计的噪声相关下的CKF可以有效地对状态进行估计,拓展了CKF的应用范围。数值仿真验证了算法的有效性。     

PARAMETER ESTIMATION METHODOLOGY FOR NONLINEAR SYSTEMS： APPLICATION TO INDUCTION MOTOR

1. Introduction In recent years, there has been a lot of research concerning parameter estimation (Akatsu and Kawamura 2000, LandauAnderson and De Bruyne 2000, Marino Peresada and Tomei 2000, Floret and Lamnabhi-Lagarrigue 2001, Pavlov and Zaremba 2001, Floret 2002, Kenné 2003). In linear systems and in some specific nonlinear cases, parameter estimation is performed using the least square algorithm (Walter and Pronzato 1994, Landau 1998). The application of this technique in the case…     

基于不完全信道信息的MIMO双向中继系统线性预编码算法#br#

针对配置两个通信节点的多输入多输出双向中继系统,提出一种基于不完全信道状态信息的预编码设计方案,该方案综合考虑信道估计误差与信道反馈延迟的情况。在中继发射功率受限的条件下,以最小均方误差为准则设计以预编码矩阵为变量的优化问题,提出矩阵分解和联合迭代两种线性预编码算法。矩阵分解法通过矩阵分解推导得到中继矩阵的闭式解;联合迭代法利用迭代算法交替迭代来联合优化预编码矩阵和接收端处理矩阵,直到算法收敛数。仿真结果表明,随着信噪比由0到25 dB逐渐增大,与现有方案相比,矩阵分解法能有效地降低系统的误比特率,联合迭代法能获得最佳的系统性能提升。     

基于影响图方法的C4ISR作战模型

影响图建模方法可对复杂系统进行规范化建模。包括C~4ISR系统的现代战争系统由武器子系统、通信子系统、指控子系统和探测子系统组成,是一类复杂系统。首先确定了表征这些子系统的参量指标,然后采用影响图方法建立了现代作战的影响图模型,进而建立了微分方程形式的C~4ISR作战模型。应用微分方程稳定性理论对C~4ISR作战模型进行分析,研究了C~4ISR系统对现代作战的影响。     

Distributed quantized consensus for agents on directed networks

Communication bandwidth and network topology are two important factors that affect performance of distributed consensus in multi-agent systems. The available works about quantized average consensus assume that the adjacency matrices associated with the digraphs are doubly stochastic, which amounts to that the digital networks are balanced. However, this assumption may be unrealistic in practice. In this paper, without assuming double stochasticity, the authors revisit an existing quantized average consensus protocol with the logarithmic quantization scheme, and investigate the quantized consensus problem in general directed digital networks that are strongly connected but not necessarily balanced. The authors first derive an achievable upper bound of the quantization precision parameter to design suitable logarithmic quantizer, and this bound explicitly depends on network topology. Subsequently, by means of the matrix transformation and the Lyapunov techniques, the authors provide a testable condition under which the weighted average consensus can be achieved with the proposed quantized protocol.     

一种改进的自适应平方根传递对准滤波算法

提出了一种解决时变噪声条件下传递对准的改进自适应平方根滤波算法。该算法将状态方差调节因子阵、自适应调节的系统噪声和量测噪声方差以及噪声有限记忆尺度融入平方根滤波结构中,采用序列算法滤波解算。算法通过一步控制和多步自适应调节过程,以较少的计算量从数值计算、噪声抑制及自适应调节方面提高滤波性能。仿真结果表明,该算法滤波稳定性强,能够根据实际噪声快速调整,且滤波精度高,为机载导弹提供了一种有效的快速精确传递对准方法。     

基于水声通信延迟的多UUV协同定位算法

针对多水下自治机器人(unmanned underwater vehicle, UUV)协同定位过程中水声通信延迟造成的定位失效问题,提出了一种基于状态估计均方误差最小的延时扩展卡尔曼滤波(delayed extended Kalman filter, DEKF)定位误差修正方法。首先建立考虑水声通信延迟的系统状态方程,利用状态转移矩阵推导系统等效量测方程,然后给出多UUV 考虑水声通信延迟的扩展卡尔曼滤波(extended Kalman filter, EKF)定位方法并分析其不足;最后在EKF方法的基础上,分析量测信息延迟对状态估计的影响,建立系统真实量测模型,设计基于状态估计均方误差最小的DEKF 算法。仿真结果表明,该方法能够有效地修正多UUV 协同定位中由于水声通信延迟造成的定位误差,在工程实践中具有一定参考意义。     

Data-Driven Leader-Follower Output Synchronization for Networked Non-Linear Multi-Agent Systems with Switching Topology and Time-Varying Delays

This paper studies the output synchronization problem for a class of networked non-linear multi-agent systems with switching topology and time-varying delays. To synchronize the outputs, a leader is introduced whose connectivity to the followers varies with time, and a novel data-driven consensus protocol based on model free adaptive control is proposed, where the reference input of each follower is designed to be the time-varying average of the neighboring agents’ outputs. Both the case when the leader is with a prescribed reference input and the case otherwise are considered. The proposed protocol allows for time-varying delays, switching topology, and does not use the agent structure or the dynamics information implicitly or explicitly. Sufficient conditions are derived to guarantee the closed-loop stability, and conditions for consensus convergence are obtained, where only a joint spanning tree is required. Numerical simulations and practical experiments are conducted to demonstrate the effectiveness of the proposed protocol.     

一种鲁棒性变步长LMS公式的稳态性能分析

介绍了一种近似最优的变步长LMS(1east mean square))公式-Shin LMS公式.并基于两点假设,对其稳态性能进行了分析,推导额外均方误差的稳态理论表达式,为该公式的应用提供了参数选择的依据.在高噪声,低噪声或者相关噪声情况下进行仿真以验证稳态分析.仿真结果表明该LMS公式均可做到收敛速度快,稳态误差小,并且能够很好的吻合理论分析的稳态结果.     

新型公交网络模型与最优出行路径算法

给出一种标号的二分图公交网络模型,在此模型基础上给出线路换乘与最优出行路径的算法,这种算法充分利用标号信息给出站点网络图的边权函数.基于站点网络图不仅能够搜索换乘线路而且能够找到最短路径.最后利用天津市部分公交系统验证了该模型及方法的有效性.     

SR-CH∞KF用于弹丸飞行姿态测量研究

为提高弹丸姿态测量精度,提出一种基于H∞滤波的平方根容积卡尔曼滤波.该方法通过三轴地磁传感器和陀螺仪组合测量模型,采用欧拉角算法模型减少状态维数并使状态方程呈现线性化,可以减少计算量.该方法可以适用于量测噪声不确定的情况,引入新息序列不断修正误差限定参数来更新量测噪声估计值,可以提高滤波的精度和鲁棒性.奇异值分解能够保...