网络化控制系统的研究现状与展望

随着网络技术的发展,网络化控制系统日益成为人们关注的课题,特别是目前工业以太网所取得的进展引起人们广泛兴趣。介绍了网络化控制系统的发展过程,在综述网络化控制系统研究现状的基础上,对网络化控制系统的建模、状态估计、信息时延、调度算法、通信约束等方面进行了深入分析,并对其中的建模、网络信息调度的最优化、网络环境下控制理论研究、应用研究等方面的未来发展作了展望。     

具有介质访问约束的网络化控制系统H∞状态估计

研究了一类存在介质访问约束和信号量化的网络化控制系统的H_∞状态估计问题。首先,考虑到介质访问约束和信号量化的影响,将信号量化误差转化为扇形有界的不确定性,对由于访问约束而未获得网络传输的系统输出采用加权补偿策略,根据网络介质的随机访问机制将网络化系统建模为具有不确定性的马尔可夫跳跃系统。然后,在此基础上借助李雅普诺夫稳定性理论和H_∞性能约束条件,利用线性矩阵不等式(linear matrix inequality,LMI)方法给出状态估计器存在的充分条件,所设计的状态估计器使得估计误差系统渐近稳定且具有给定的H_∞性能。最后,通过仿真实例验证了该设计方法的有效性。     

基于输出反馈的不确定NCS鲁棒容错控制

研究了一类具有网络诱导时延和参数不确定性网络化控制系统鲁棒容错控制问题.基于将时延的不确定性转换为系统状态方程系数矩阵不确定性的NCS模型,同时考虑系统参数不确定性对系统的影响,应用Lyapunov稳定性理论和LMI方法,采用输出反馈控制策略,推证出了保证闭环网络化控制系统在执行器或传感器发生故障时仍渐进稳定的充分条件,并以求解线性矩阵不等式组给出了容错控制器的设计方法,最后用仿真算例验证了此方法的可行性和有效性.     

基于输出反馈网络化控制系统鲁棒容错控制

研究了一类具有时延不确定性的网络化控制系统的鲁棒容错控制问题.针对以往控制器大多采用状态反馈的形式,而对功能和结构复杂的网络化控制系统全部状态往往难于测取,因而状态反馈形式的控制器在应用中会受到限制,完整性问题的结果也主要基于0-1故障模型.采用动态输出反馈控制策略,针对网络化控制系统的时延和不同步对系统产生的影响,基...     

基于NCS时延模型的鲁棒容错控制器

研究了一类具有未知扰动和参数不确定性的网络化控制系统的鲁棒容错控制问题.针对NCS的时延和不同步对系统产生的影响,基于将时延的不确定性转换为系统状态方程系数矩阵不确定性的NCS模型,同时考虑系统参数不确定性和未知扰动对系统的影响,应用Lyapunov稳定性理论和LMI方法,采用状态反馈控制策略,推证出了保证闭环网络化控制系统在执行器或传感器发生失效故障时仍渐近稳定的充分条件,并通过求解线性矩阵不等式组方便地得到了容错控制器的设计方法,最后用仿真算例验证了此方法的可行性和有效性.     

一类诱导时滞网络控制系统自抗扰控制器设计

针对一类具有网络时滞小于采样周期的网络控制系统提出网络控制的主要问题是网络通信系统模型的不确定性导致控制性能不佳;针对这一问题,采用基于无模型的自抗扰算法,将网络环节和被控对象一同视为控制对象,将网络时滞作为被控对象的不确定性因素,利用扩张状态观测器对不确定性因素进行实时观测估计;Matlab/TrueTime网络控制实验表明:自抗扰控制方法能够有效地减小网络诱导时滞对控制系统的影响。     

基于Rabbit2000的网络化控制系统设计

针对嵌入式系统的实时网络化控制的难度,设计了一套通过互联网对嵌入式设备实现实时在线的控制系统.该系统中,每个被控设备由单片机控制,通过RS-485总线和一个单片机系统组成一个控制系统网络,最后使单片机和Rabbit2000串口通信,实现系统的网络化控制.实践证明,嵌入式设备和网络技术的结合使设备的控制更加智能化.     

网络化工业控制系统的研究进展

工业控制系统已跨入网络化控制的新阶段,网络化工业控制系统已成为制造业控制、过程控制和测控技术等领域中的重要研究方向.阐述了网络化工业控制系统设计和实现中的一些主要问题,包括:网络化工业控制系统的体系结构、时延问题、时钟同步、控制算法以及节点测控器等问题;提出了网络化工业控制系统进一步研究的一些问题.     

带未知通信干扰和丢包补偿的多传感器网络化不确定系统的分布式融合滤波

研究了带有未知通信干扰、观测丢失和乘性噪声不确定性的多传感器网络化系统的状态估计问题.通过白色乘性噪声描述系统状态和观测中的随机不确定性,采用一组服从Bernoulli分布的随机变量描述网络传输过程中存在的观测丢失现象,且数据传输中存在未知的网络通信干扰.当发生丢包时,以当前丢失观测的预报值进行补偿.对每个单传感器子系统,应用线性无偏最小方差估计准则设计了不依赖于未知通信干扰的最优线性滤波器.推导了任两个局部滤波误差之间的互协方差阵.进而,应用矩阵加权融合估计算法给出了分布式融合状态滤波器.仿真例子验证了算法的有效性.     

过程控制的网络化发展趋势综述

从过程控制技术的发展历程和实际的控制应用需求探讨了控制网络化的必然性及控制系统与信息通信密不可分的关系,阐述了控制网络化的体系结构和特点,分析了控制网络化对相关产业链的影响.针对控制网络化对传统控制系统开发技术的挑战,提出了解决方案和应对策略,并指出工业过程控制系统必须便于实现与企业中监控调度、管理决策等系统的集成,以系统集成促进工控技术的发展,从而对于继续开展控制网络化方面的研究具有一定的借鉴作用.     

一种噪声和畸变混沌信号的滤波策略-Ⅱ：自适应解调

在这系列文章的第一部分，我们提出了一种状态空间模型的估计算法。第二部分将该算法应用于混沌调制通信系统的解调。当“扮演”系统参数的信息信号被建模为AR模型后，混沌调制通信系统的解调问题可转化为对增广的状态空间模型的估计。仿真结果表明，该算法也能有效地实现混沌调制通信系统的自适应解调。     

A distributed control and parameter estimation protocol with prescribed performance for homogeneous lagrangian multi-agent systems

In this paper, we consider the formation control problem for uncertain homogeneous Lagrangian nonlinear multi-agent systems in a leader-follower scheme under a directed communication protocol. A distributed adaptive control protocol of minimal complexity is proposed that achieves prescribed, arbitrarily fast and accurate formation establishment as well as synchronization of the parameter estimates of all followers. The estimation and control laws are distributed in the sense that the control signal and the update laws are calculated based solely on local relative state information. Moreover, provided that the communication graph is strongly connected and contrary to the related works on multi-agent systems, the controller-imposed transient and steady state performance bounds are fully decoupled from: (i) the underlying graph topology, (ii) the control gains selection and (iii) the agents’ model uncertainties. Finally, extensive simulation studies on the attitude control of flying spacecrafts clarify and verify the approach.     

Observer-enhanced distributed moving horizon state estimation subject to communication delays

In this work, we focus on distributed moving horizon estimation (DMHE) of nonlinear systems subject to time-varying communication delays. In particular, a class of nonlinear systems composed of subsystems interacting with each other via their states is considered. In the proposed design, an observer-enhanced moving horizon state estimator (MHE) is designed for each subsystem. The distributed MHEs exchange information via a shared communication network. To handle communication delays, an open-loop state predictor is designed for each subsystem to provide predictions of unavailable subsystem states (due to delays). Based on the predictions, an auxiliary nonlinear observer is used to generate a reference subsystem state estimate for each subsystem. The reference subsystem state estimate is used to formulate a confidence region for the actual subsystem state. The MHE of a subsystem is only allowed to optimize its subsystem state estimate within the corresponding confidence region. Under the assumption that there is an upper bound on the time-varying delays, the proposed DMHE is proved to give decreasing and ultimately bounded estimation error. The theoretical results are illustrated via the application to a reactor–separator chemical process.     

Cross-estimator design for coordinated systems: Constraints, covariance, and communications resource assignment

Coordinated systems interact via the exchange of information through communication. As the network of coordinated systems increases in the number of subsystems, natural limits on the available bandwidth of communication need to be imposed. Without this, the coordinated system does not scale properly and the interaction burden becomes unmanageable. Our aim in this paper is to develop estimation techniques for the coordinated systems including the allocation of communication resources. Central ideas involve: interaction via constraints imposed by neighbors, the tightening of these constraints to reflect state uncertainty, and the assignment of communications resources to manage this uncertainty in the estimator design. Linear matrix inequality methods are applied to develop a solution which links control objective, performance, and communication limits.     

Event-based control and filtering of networked systems: A survey

In recent years, theoretical and practical research on event-based communication strategies has gained considerable research attention due primarily to their irreplaceable superiority in resource-constrained systems (especially networked systems). For networked systems, event-based transmission scheme is capable of improving the efficiency in resource utilization and prolonging the lifetime of the network components compared with the widely adopted periodic transmission scheme. As such, it would be interesting to 1) examining how the event-triggering mechanisms affect the control or filtering performance for networked systems, and 2) developing some suitable approaches for the controller and filter design problems. In this paper, a bibliographical review is presented on event-based control and filtering problems for various networked systems. First, the event-driven communication scheme is introduced in detail according to its engineering background, characteristic, and representative research frameworks. Then, different event-based control and filtering (or state estimation) problems are categorized and then discussed. Finally, we conclude the paper by outlining future research challenges for event-based networked systems.     

Active fault tolerant control for switched positive linear systems

The main aim of this paper is to design an active fault tolerant controller for switched positive linear systems. A theorem is proved for fault and state estimation of switched positive linear systems in terms of matrix inequality by considering average dwell‐time approach. By utilizing the theorem results, not only a fast and exact estimation of fault and state is obtained but also the positivity of state estimation is ensured. The feasibility problem is solved by formulating it into a special sequential optimization problem subject to LMI constraints. Based on the fault estimation information, an observer‐based fault tolerant control guaranties the stability and positivity of the closed‐loop system. Finally, a practical example including a data communication network is presented to illustrate the efficiency of the proposed method.     

Average Consensus for Multi‐Agent System with Measurement Noise and Binary‐Valued Communication

This paper considers the average consensus problems of a class of multi‐agent systems (MAS) with binary‐valued communication. Each agent can only obtain its neighbor's binary‐valued information under measurement noise because of limited bandwidth in communication channels. To seek consensus, we propose a two‐scale multi‐agent consensus algorithm with distributed strategy by combining state estimation and control design alternately. An exponential step size is chosen in the state estimation process and the estimation method can be proved to be asymptotically efficient. Additionally, by utilizing a distributed control law designed based on the estimates of the neighbors' states with a constant gain, we further prove that the proposed average consensus algorithm is convergent. Furthermore, the proposed average consensus algorithm is given and proved. Finally, some simulation results, which illustrate the effectiveness of the obtained results, are also given in the paper.     

State estimation with communication constraints

Information processing and system estimation and control are commonly regarded as two separate research areas. In this paper, we investigate a simple state estimation problem which involves a communication channel with finite bandwidth for transmitting remotely obtained data before it can be processed. If the a priori distribution of the process is shifted Laplacian, then a lower bound on the data transmission rate is obtained to ensure that the estimation sequence is convergent in quadratic mean to the sampled state sequence, thus relating the communication channel constraint with the underlying system dynamics.     

Minimal sensor activation and minimal communication in discrete-event systems

This paper is an overview of the current research on minimal sensor activation and minimal communication in discrete-event systems. In problems of sensor activation agents observing a discrete-event system can turn the sensors for their observable events on or off dynamically. In problems of communication agents observing a discrete-event system can communicate event observations to one another dynamically. In both cases, a result is that the observations made by an agent are dynamic. That is, whether or not an agent observes an event or receives a communication is dependent on other factors besides membership of certain events to certain predefined sets. We survey such problems and associated works where, additionally, the use of event sensors and communication of messages must be minimized with respect to certain criteria. The application areas considered are the diagnosis, state disambiguation and state estimation of discrete-event systems.