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类型 基础研究 预答辩日期 2018-04-12
开始(开题)日期 2016-06-03 论文结束日期 2017-12-27
地点 中心楼609 论文选题来源 973、863项目     论文字数 6.0 (万字)
题目 多主体结构刻画与分布式估计研究
主题词 多主体系统,结构可控性,一致性,分布式估计,协同可观测性
摘要 随着传感器技术、网络技术和计算机技术等的快速发展, 多主体系统和分布式估计已成为控制领域的研究热点, 其应用前景引起学术界和工业界的普遍关注。 多主体系统通过个体间的协调控制来实现单个个体无法完成的复杂任务, 具有容错性、灵活性和鲁棒性等特点。 多主体系统的能控性设计和领导选择在多车辆编队、自主水下航行器、 智能交通和卫星姿态协同控制等工程领域已有广泛应用。 同时,分布式估计算法不依赖于集中传感器, 具有可扩展性的优点且能够适应不同环境的变化,在实际领域得到了广泛应用,如目标跟踪、空间碎片确定、 环境污染监测和视频网络监控等。 本文主要基于图论研究了网络化分布式系统的结构可控性、协同可观性、以及分布式滤波器设计问题。 一方面研究了如何选择领导节点使得多主体系统强结构可控; 并进一步扩展到需要测量信息的网络,分析了传感器的布控问题。 另一方面,对于分布式估计问题,分析了强连通通信条件下网络的协同可观性, 分别对线性和非线性系统设计了具有有限步精确一致的分布式信息Kalman滤波器和无迹Kalman滤波器。 文中涉及到的分析工具包括图论、组合优化、线性系统和最优估计理论。 论文的主要内容如下: 1. 基于图论研究多主体系统在结构化意义下的领导或测量选择问题。 针对一阶积分器多主体系统,将此系统刻画成线性时不变系统, 通过选择领导者使得多主体系统为强结构可控的。 给出两类特殊的结构,证明这两类拓扑所需要的领导者数目为$1$, 并指出一般任意有向拓扑可分割为此两类拓扑,从而可以根据此分割来选择领导者, 同时分析了几类拓扑在某些主体失效的情形下仍能保证系统为强结构可控的领导者数目。 对于存在测量并利用测量值设计输出反馈控制器时的多主体系统, 将此系统转化为秩$1$双线性结构化系统, 此时通过选取领导者和测量主体使得该系统为结构可控的。 将此问题进一步转化为进行控制断面设计的优化问题,引入有向非圈图和二分图分解并定义动态图, 分别用来验证结构可控时的输入和输出可达行、满秩和互素路径条件, 借此给出具有最小代价约束时的断面求解方法。 2. 研究传感器网络的分布式估计协议设计问题。 首先,证明了一类基于分布式观测器协议的存在性, 并分析了实现状态重构时,该协议的参数与网络拓扑结构的关系。 针对噪声存在时的线性系统, 利用双时标设计技术对信息型Kalman滤波器的新息向量和新息矩阵进行有限步融合, 并通过构造次优估计器的方法证明了协同观测性条件下该分布式信息型Kalman滤波器的稳定性。 当目标建模为非线性随机系统时,设计递推类型的估计器来实现对目标状态的重构。 非线性关系较弱时,可通过线性化来设计基于最大一致的分布式扩展Kalman滤波器; 系统具有强非线性关系时,利用传感器节点自身的存储数据, 完全分布式地构造出一致滤波状态和协方差矩阵,从而得到分布式无迹Kalman滤波器。
英文题目 Structure Depiction of multi-agent systems and distributed estimation
英文主题词 multi-agent systems, structural controllability, consensus, distributed estimate, cooperative observability
英文摘要 With the rapid development of sensor technology, network technology and computer technology, the multi-agent systems and distributed estimation have become the research focus in the fields of control theory and application. Which are attracting the attention of the academia and industry due to their potential application. The multi-agent systems can accomplish the complex tasks via the coordinated control while the single individual cannot do. They have the characteristics of fault tolerance, flexibility and robustness. The design of controllability and leader selection of multi-agent systems have been applied in engineering fields such as multi-vehicle formation, autonomous underwater vehicle, intelligent transportation and satellite attitude cooperative control. At the same time, the distributed estimation algorithms are not dependent on the center sensors. They have the advantage of scalability and can adapt to the varying environment. Up to now, the idea of distributed estimation has found wide applications in many practical fields, such as target tracking, the determination of space debris, environment pollution monitoring and camera network monitoring, etc. This dissertation mainly studies the structural controllability of networked distributed systems, cooperative observability and the design of distributed filter. On the one hand, it studies how to select the leaders such that the multi-agent systems are strongly structurally controllable. Furthermore, we consider the issue that the measurements are needed in multi-agent systems. Then the placement of sensors are discussed. On the other hand, we analyze the cooperative observability for the distributed estimation problem under the strongly connected network. Next, we present the distributed information Kalman filter and distributed unscented Kalman filter for the linear and nonlinear systems respectively. These two filters are based on accurate consensus protocols with finite iteration steps. The main analysis tools utilized in this dissertation include graph theory, combinatorial optimization, linear system theory and optimal estimate. The main contents of the dissertation are summarized as follows: 1. The graph theory is used to select the leaders or measurements for multi-agent systems in the structural sense. For the multi-agent systems that can be transformed into a general linear time invariant system, the multi-agent systems will be strongly structurally controllable via selecting the leaders. We prove that the topologies of path and path-bud only need one leader to guarantee the strong structural controllability. Then we point out that any directed graph can be partitioned into disjoint paths and path-buds, and the leaders are the root agents of all paths. We also discuss the strong structural controllability of bidirectional path and grounded tree with the failure of any one node. The minimum number and position of the leaders for these two special topologies are provided. When some agents’ states can be measured in multi-agent systems, we consider the case that the system can be transformed into a bilinear structured system with rank $1$. This system is structurally controllable by choosing the leaders and the measurement agents. This problem is equivalent to an optimization problem on configuration design. In order to resolve this optimization problem, we introduce the directed acyclic graph decomposition, bipartite graph decomposition and dynamic graph. They are used to verify the input and output accessibility, full rank condition and coprime paths property. A method is given to provide the optimal solution to minimum cost control configuration design problem. 2. The design methods of distributed estimation protocols are explored for wireless sensor networks. For the case of heterogeneous sensors, the existence of a type of distributed observer protocol is proved. The relationship between the parameters of the protocol and the network topology is analyzed when the state reconstruction is realized. For linear system with state noise and measurement noise, a distributed information Kalman filter is proposed which is based on the finite fusion of innovation vector and innovation matrix. This is the two time scale design strategy. We assume that all sensors are cooperative observable. Then the stability of this filter is proved by constructing suboptimal estimator method. When the target is modeled as a nonlinear stochastic system, the recursive estimator is designed to estimate the state of the target. If the nonlinear relationship is weaker, the distributed extended Kalman filter can be used to get the approximate state. If the nonlinear relationship is stronger, the distributed unscented Kalman filter is designed to track the plant. The consensus filtering state and covariance matrix are obtained by using the storage data of each sensor.
学术讨论
主办单位时间地点报告人报告主题
复杂工程系统测量与控制实验室 2013.04 中心楼609会议室 邵敬平 Cooperative Source Localization of Multi-agent Systems with a Cooperatively PE Condition
复杂工程系统测量与控制实验室 2013.05 中心楼609会议室 曹青青 ATS推导skew的均值和方差
复杂工程系统测量与控制实验室 2012.06 中心楼609会议室 刘鹏 内省个体网络的输出一致及常时滞异构网络的同步
复杂工程系统测量与控制实验室 2013.10 中心楼609会议室 刘鹏 Conditions for detectability in distributed consensus-based observer networks
复杂工程系统测量与控制实验室 2014.10 中心楼609会议室 刘鹏 Zero forcing sets and Controllability of Dynamical Systems Defined on Graphs
复杂工程系统测量与控制实验室 2016.02 中心楼609会议室 刘鹏 基于图论的多智能体结构刻画与分布式估计问题研究
东南大学 数学学院 2012.05 数学系第一报告厅 曹明 Clock synchronization in distributed networks
东南大学 自动化学院 2017.10 中心楼二楼教育部重点实验室会议室 Brian D. O Anderson The Mathematics of Formation Control
     
学术会议
会议名称时间地点本人报告本人报告题目
The 2015 Chinese Intelligent Systems Conference 2015.10.17 扬州 Strong Structural Controllability and Leader Selection for Multi-agent Systems with Unidirectional Topology
The 13th IEEE International Conference on Control & Automation 2017.07.04 Ohrid Scheduling Algorithm of Observation and Controlling for Multi-Agent Systems to Guarantee Structural Controllability
     
代表作
论文名称
Leader Selection for Strong Structural Controllability of Single-Integrator Multi-Agent Systems
Strong Structural Controllability and Leader Selection for Multi-agent Systems with Unidirectional T
 
答辩委员会组成信息
姓名职称导师类别工作单位是否主席备注
徐胜元 正高 教授 博导 南京理工大学
达飞鹏 正高 教授 博导 东南大学
朱建栋 正高 教授 博导 南京师范大学
李新德 正高 教授 博导 东南大学
李俊 副高 副教授 博导 东南大学
      
答辩秘书信息
姓名职称工作单位备注
陈杨杨 副高 副教授 东南大学