一类Lipschitz非线性随机网络化控制系统稳定与控制
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摘要
网络化控制系统(Networked Control System,简称NCS)的研究已经成为当前自动化领域中的一个热点,网络化控制系统是一种通过共享的通讯网络将传感器,执行器和控制器连接在一起的分布式控制系统。将网络引入控制系统,连接智能现场设备和自动化系统,实现了现场设备控制的分布化和网络化,加强了现场控制和上层管理的联系,从而改善了生产过程的安全性、可靠性、效率和消耗等性能。网络的引入同时也产生了一些新问题:例如网络时延、数据丢包等。众所周知,实际系统中常存在非线性,且许多实际非线性系统满足Lipschitz条件,如含有三角函数非线性项的机器人或飞行器控制系统等。Lipschitz非线性系统是指系统中关于状态与输入的非线性环节相对于系统的状态变量满足Lipschitz条件的非线性系统。因此关于Lipschitz非线性网络化控制系统的研究在理论和应用上是非常重要的,同时也是非常具有代表性和挑战性的问题。本文主要针对一类存在随机数据丢包或随机网络诱导时延的Lipschitz非线性网络化控制系统的指数稳定和控制器设计进行了深入的探讨和研究。
首先,本文全面而简要地介绍了NCS的起源、发展、特点以及目前的研究现状。详细地分析了NCS中的若干基本问题、典型研究方法,同时提出了本文对NCS相关研究工作的观点和看法,主要的研究工作包括:
1.针对传感器-控制器和控制器-执行器通道存在随机数据包丢失的Lipschitz非线性网络化控制系统,用满足Bernoulli分布的二进制切换序列来描述随机数据包丢失,并建立模型。依据李雅普诺夫稳定性理论,给出了一个基于线性矩阵不等式(LMI)的闭环系统均方指数稳定的充分条件。进一步地给出了使闭环非线性网络控制系统均方指数稳定,且满足指定H_∞性能指标的基于观测器的动态输出反馈控制器存在的充分条件,给出了设计基于观测器的控制器的线性矩阵不等式(LMI)方法,并转化为一类具有线性矩阵不等式约束的凸优化问题,通过求解建立的凸优化问题得到Lipschitz非线性网络化控制系统的扰动抑制最优控制器。最后用一个数值算例验证了提出的方法的有效性。
2.针对传感器-控制器和控制器-执行器通道存在随机时延的Lipschitz非线性网络化控制系统,用满足Bernoulli分布的二进制切换序列来描述随机时延,并建立模型。利用李雅普诺夫稳定性理论,给出了一个基于线性矩阵不等式(LMI)的闭环系统指数均方稳定的充分条件。进一步地给出了使闭环Lipschitz非线性网络控制系统均方指数稳定,且满足指定H_∞性能指标的基于观测器的动态输出反馈控制器存在的充分条件,给出了设计基于观测器的控制器的线性矩阵不等式(LMI)方法,并转化为一类具有线性矩阵不等式约束的凸优化问题,通过求解建立的凸优化问题得到Lipschitz非线性网络化控制系统的扰动抑制最优控制器。最后用一个数值算例验证了提出的方法的有效性。
3.针对具有独立随机丢包概率的多传感器Lipschitz非线性网络化控制系统,认为空间分布不同的多个传感器具有独立的工作特性,即每个传感器到控制器通道发生数据包丢失的概率是不同的,也是互相独立的。同时考虑传感器-控制器和控制器-执行器通道的随机丢包,用满足Bernoulli分布的二进制切换序列来描述随机数据包丢失,并建立模型。利用李雅普诺夫稳定性理论,给出了一个基于线性矩阵不等式(LMI)的闭环系统均方指数稳定的充分条件。进一步地给出了使闭环Lipschitz非线性网络控制系统均方指数稳定,且满足指定H_∞性能指标的基于观测器的动态输出反馈控制器存在的充分条件,给出了设计基于观测器的控制器的线性矩阵不等式(LMI)方法,并转化为一类具有线性矩阵不等式约束的凸优化问题,通过求解建立的凸优化问题得到Lipschitz非线性网络化控制系统的扰动抑制最优控制器。最后用一个数值算例验证了提出的方法的有效性。
4.针对具有独立随机时延概率的多传感器Lipschitz非线性网络化控制系统,认为空间分布不同的多个传感器具有独立的工作特性,即每个传感器到控制器通道发生时延的概率是不同的,也是互相独立的。同时考虑传感器-控制器和控制器-执行器通道的随机时延,用满足Bernoulli分布的二进制切换序列来描述随机时延,并建立模型。利用李雅普诺夫稳定性理论,给出了一个基于线性矩阵不等式(LMI)的闭环系统均方指数稳定的充分条件。进一步地给出了使闭环Lipschitz非线性网络控制系统均方指数稳定,且满足指定H_∞性能指标的基于观测器的动态输出反馈控制器存在的充分条件,给出了设计基于观测器的控制器的线性矩阵不等式(LMI)方法,并转化为一类具有线性矩阵不等式约束的凸优化问题,通过求解建立的凸优化问题得到Lipschitz非线性网络化控制系统的扰动抑制最优控制器。最后用一个数值算例验证了提出的方法的有效性。
Networked control systems (NCSs) have been studied intensively in theautomatic control field in the past a few years. NCSs are spatially distributedsystems in which the communication between sensors, actuators, and con-trollers occurs through a shared bandlimited digital communication network.Such NCSs make it possible to share process data and marketing informationplant-widely, which improves availability, operating safety, reliability and en-vironment protection of the production. In the control of NCSs, there aremany new problems such as the intermittent data packet losses, the network-induced time delay, and communication constrains. The intermittent datapacket losses and the network-induced time delay are known to be two ofthe main causes for the performance deterioration or even the instability ofthe controlled networked system. It is well-known that there commonly existthe nonlinearities in practical control systems, and most of the nonlineari-ties satisfy the Lipschitz condition, for example, the trigonometric functionnonlinearities in the robot and the Aircraft Systems. Lipschitz nonlinearsystems is a kind of nonlinear systems system which the nonlinear compo-nents of the state and input relative to the system state variables satisfythe Lipschitz condition. So the research about networked nonlinear systemswith Lipschitz is very important both in theories and applications, and also avery representative and challenging problem. We thoroughly investigate thestability-analysis and controller-synthesis problems of networked nonlinearsystems with global Lipschitz nonlinearities with random packet dropout orrandom network-induced time delay. The main contents are as follows:
Firstly, this paper introduce the origin、development、specialty and thecurrent research status of NCSs roundly and detailedly, and analyze theseveral base problem、typical research approaches, and at the same time we advance our opinion about the research of NCSs. The contributions of theworks are listed in the following.
1. The observer-based H_∞control problem of networked nonlinearsystems with global Lipschitz nonlinearities and with the random packetlosses in both the sensor-to-controller and sensor-to-controller communica-tion channels is investigated. The random packet loss is modelled as aBernoulli distributed white sequence with a known conditional probabilitydistribution. In the presence of random packet losses, based on the Lyapunovstability theory, su?cient conditions for the existence of an observer-basedfeedback controller are derived, such that the closed-loop networked nonlin-ear system is exponentially stable in the sense of mean square and a pre-scribed H_∞disturbance-rejection-attenuation performance is also achieved.And then an linear matrix inequality (LMI) approach for designing such anobserver-based H_∞controller is presented by solving a certain convex opti-mization problem. Finally, a simulation example is used to demonstrate thee?ectiveness of the proposed method.
2. The observer-based H_∞control problem of networked nonlinear sys-tems with global Lipschitz nonlinearities and with the random communica-tion delays in both the sensor-to-controller and sensor-to-controller commu-nication channels is explored. The random communication delays is mod-elled as a Bernoulli distributed white sequence with a known conditionalprobability distribution. In the presence of communication delays, based onthe Lyapunov stability theory, su?cient conditions for the existence of anobserver-based feedback controller are derived, such that the closed-loop net-worked nonlinear system is exponentially stable in the sense of mean squareand a prescribed H_∞disturbance-rejection-attenuation performance is alsoguaranteed. And then an linear matrix inequality (LMI) approach for de-signing such observer-based H_∞controller is presented. With the help ofthe LMI solvers, the observer-based H_∞controller can easily be obtained bysolving a certain convex optimization problem. Finally, a simulation example is used to demonstrate the effectiveness of the proposed method.
3. The observer-based H_∞control problem of networked nonlinear sys-tems with global Lipschitz nonlinearities and with multiple sensors with dif-ferent packet losses probabilities is studied. It is supposed that in the commu-nication channels from the multiple sensors to the controller each sensor hasan individual random data missing probability. The random packet loss ismodelled as a Bernoulli distributed white sequence with a known conditionalprobability distribution. In the presence of random multiple packet losses,based on the Lyapunov stability theory, su?cient conditions for the existenceof an observer-based feedback controller are derived, such that the closed-loop networked nonlinear system is exponentially stable in the sense of meansquare and a prescribed H_∞disturbance-rejection-attenuation performanceis also guaranteed. And then an linear matrix inequality (LMI) approach fordesigning such observer-based H_∞controller is presented. With the help ofthe LMI solvers, the observer-based H_∞controller can easily be obtained bysolving a certain convex optimization problem. Finally, a simulation exampleis used to demonstrate the e?ectiveness of the proposed method.
4. The observer-based H_∞control problem of networked nonlinear sys-tems with global Lipschitz nonlinearities and with random multiple com-munication delays is investigated. Because of the limited bandwidth of thechannels, such random communication delays could occur, simultaneously, inthe communication channels from the multiple sensors to the controller andfrom the controller to the actuator. It is supposed that in the communica-tion channels from the multiple sensors to the controller each sensor has anindividual random delay probability. The random communication delay ismodelled as a Bernoulli distributed white sequence with a known conditionalprobability distribution. In the presence of random multiple communicationdelays, based on the Lyapunov stability theory, su?cient conditions for theexistence of an observer-based feedback controller are derived, such that theclosed-loop networked nonlinear system is exponentially stable in the sense of mean square and a prescribed H_∞disturbance-rejection-attenuation perfor-mance is also achieved. And then a linear matrix inequality (LMI) approachfor designing such an observer-based H_∞controller is presented. With thehelp of the LMI solvers, the observer-based H_∞controller can easily be ob-tained by solving a certain convex optimization problem. Finally, a numericalexample is used to demonstrate the e?ectiveness of the proposed method.
首先,本文全面而简要地介绍了NCS的起源、发展、特点以及目前的研究现状。详细地分析了NCS中的若干基本问题、典型研究方法,同时提出了本文对NCS相关研究工作的观点和看法,主要的研究工作包括:
1.针对传感器-控制器和控制器-执行器通道存在随机数据包丢失的Lipschitz非线性网络化控制系统,用满足Bernoulli分布的二进制切换序列来描述随机数据包丢失,并建立模型。依据李雅普诺夫稳定性理论,给出了一个基于线性矩阵不等式(LMI)的闭环系统均方指数稳定的充分条件。进一步地给出了使闭环非线性网络控制系统均方指数稳定,且满足指定H_∞性能指标的基于观测器的动态输出反馈控制器存在的充分条件,给出了设计基于观测器的控制器的线性矩阵不等式(LMI)方法,并转化为一类具有线性矩阵不等式约束的凸优化问题,通过求解建立的凸优化问题得到Lipschitz非线性网络化控制系统的扰动抑制最优控制器。最后用一个数值算例验证了提出的方法的有效性。
2.针对传感器-控制器和控制器-执行器通道存在随机时延的Lipschitz非线性网络化控制系统,用满足Bernoulli分布的二进制切换序列来描述随机时延,并建立模型。利用李雅普诺夫稳定性理论,给出了一个基于线性矩阵不等式(LMI)的闭环系统指数均方稳定的充分条件。进一步地给出了使闭环Lipschitz非线性网络控制系统均方指数稳定,且满足指定H_∞性能指标的基于观测器的动态输出反馈控制器存在的充分条件,给出了设计基于观测器的控制器的线性矩阵不等式(LMI)方法,并转化为一类具有线性矩阵不等式约束的凸优化问题,通过求解建立的凸优化问题得到Lipschitz非线性网络化控制系统的扰动抑制最优控制器。最后用一个数值算例验证了提出的方法的有效性。
3.针对具有独立随机丢包概率的多传感器Lipschitz非线性网络化控制系统,认为空间分布不同的多个传感器具有独立的工作特性,即每个传感器到控制器通道发生数据包丢失的概率是不同的,也是互相独立的。同时考虑传感器-控制器和控制器-执行器通道的随机丢包,用满足Bernoulli分布的二进制切换序列来描述随机数据包丢失,并建立模型。利用李雅普诺夫稳定性理论,给出了一个基于线性矩阵不等式(LMI)的闭环系统均方指数稳定的充分条件。进一步地给出了使闭环Lipschitz非线性网络控制系统均方指数稳定,且满足指定H_∞性能指标的基于观测器的动态输出反馈控制器存在的充分条件,给出了设计基于观测器的控制器的线性矩阵不等式(LMI)方法,并转化为一类具有线性矩阵不等式约束的凸优化问题,通过求解建立的凸优化问题得到Lipschitz非线性网络化控制系统的扰动抑制最优控制器。最后用一个数值算例验证了提出的方法的有效性。
4.针对具有独立随机时延概率的多传感器Lipschitz非线性网络化控制系统,认为空间分布不同的多个传感器具有独立的工作特性,即每个传感器到控制器通道发生时延的概率是不同的,也是互相独立的。同时考虑传感器-控制器和控制器-执行器通道的随机时延,用满足Bernoulli分布的二进制切换序列来描述随机时延,并建立模型。利用李雅普诺夫稳定性理论,给出了一个基于线性矩阵不等式(LMI)的闭环系统均方指数稳定的充分条件。进一步地给出了使闭环Lipschitz非线性网络控制系统均方指数稳定,且满足指定H_∞性能指标的基于观测器的动态输出反馈控制器存在的充分条件,给出了设计基于观测器的控制器的线性矩阵不等式(LMI)方法,并转化为一类具有线性矩阵不等式约束的凸优化问题,通过求解建立的凸优化问题得到Lipschitz非线性网络化控制系统的扰动抑制最优控制器。最后用一个数值算例验证了提出的方法的有效性。
Networked control systems (NCSs) have been studied intensively in theautomatic control field in the past a few years. NCSs are spatially distributedsystems in which the communication between sensors, actuators, and con-trollers occurs through a shared bandlimited digital communication network.Such NCSs make it possible to share process data and marketing informationplant-widely, which improves availability, operating safety, reliability and en-vironment protection of the production. In the control of NCSs, there aremany new problems such as the intermittent data packet losses, the network-induced time delay, and communication constrains. The intermittent datapacket losses and the network-induced time delay are known to be two ofthe main causes for the performance deterioration or even the instability ofthe controlled networked system. It is well-known that there commonly existthe nonlinearities in practical control systems, and most of the nonlineari-ties satisfy the Lipschitz condition, for example, the trigonometric functionnonlinearities in the robot and the Aircraft Systems. Lipschitz nonlinearsystems is a kind of nonlinear systems system which the nonlinear compo-nents of the state and input relative to the system state variables satisfythe Lipschitz condition. So the research about networked nonlinear systemswith Lipschitz is very important both in theories and applications, and also avery representative and challenging problem. We thoroughly investigate thestability-analysis and controller-synthesis problems of networked nonlinearsystems with global Lipschitz nonlinearities with random packet dropout orrandom network-induced time delay. The main contents are as follows:
Firstly, this paper introduce the origin、development、specialty and thecurrent research status of NCSs roundly and detailedly, and analyze theseveral base problem、typical research approaches, and at the same time we advance our opinion about the research of NCSs. The contributions of theworks are listed in the following.
1. The observer-based H_∞control problem of networked nonlinearsystems with global Lipschitz nonlinearities and with the random packetlosses in both the sensor-to-controller and sensor-to-controller communica-tion channels is investigated. The random packet loss is modelled as aBernoulli distributed white sequence with a known conditional probabilitydistribution. In the presence of random packet losses, based on the Lyapunovstability theory, su?cient conditions for the existence of an observer-basedfeedback controller are derived, such that the closed-loop networked nonlin-ear system is exponentially stable in the sense of mean square and a pre-scribed H_∞disturbance-rejection-attenuation performance is also achieved.And then an linear matrix inequality (LMI) approach for designing such anobserver-based H_∞controller is presented by solving a certain convex opti-mization problem. Finally, a simulation example is used to demonstrate thee?ectiveness of the proposed method.
2. The observer-based H_∞control problem of networked nonlinear sys-tems with global Lipschitz nonlinearities and with the random communica-tion delays in both the sensor-to-controller and sensor-to-controller commu-nication channels is explored. The random communication delays is mod-elled as a Bernoulli distributed white sequence with a known conditionalprobability distribution. In the presence of communication delays, based onthe Lyapunov stability theory, su?cient conditions for the existence of anobserver-based feedback controller are derived, such that the closed-loop net-worked nonlinear system is exponentially stable in the sense of mean squareand a prescribed H_∞disturbance-rejection-attenuation performance is alsoguaranteed. And then an linear matrix inequality (LMI) approach for de-signing such observer-based H_∞controller is presented. With the help ofthe LMI solvers, the observer-based H_∞controller can easily be obtained bysolving a certain convex optimization problem. Finally, a simulation example is used to demonstrate the effectiveness of the proposed method.
3. The observer-based H_∞control problem of networked nonlinear sys-tems with global Lipschitz nonlinearities and with multiple sensors with dif-ferent packet losses probabilities is studied. It is supposed that in the commu-nication channels from the multiple sensors to the controller each sensor hasan individual random data missing probability. The random packet loss ismodelled as a Bernoulli distributed white sequence with a known conditionalprobability distribution. In the presence of random multiple packet losses,based on the Lyapunov stability theory, su?cient conditions for the existenceof an observer-based feedback controller are derived, such that the closed-loop networked nonlinear system is exponentially stable in the sense of meansquare and a prescribed H_∞disturbance-rejection-attenuation performanceis also guaranteed. And then an linear matrix inequality (LMI) approach fordesigning such observer-based H_∞controller is presented. With the help ofthe LMI solvers, the observer-based H_∞controller can easily be obtained bysolving a certain convex optimization problem. Finally, a simulation exampleis used to demonstrate the e?ectiveness of the proposed method.
4. The observer-based H_∞control problem of networked nonlinear sys-tems with global Lipschitz nonlinearities and with random multiple com-munication delays is investigated. Because of the limited bandwidth of thechannels, such random communication delays could occur, simultaneously, inthe communication channels from the multiple sensors to the controller andfrom the controller to the actuator. It is supposed that in the communica-tion channels from the multiple sensors to the controller each sensor has anindividual random delay probability. The random communication delay ismodelled as a Bernoulli distributed white sequence with a known conditionalprobability distribution. In the presence of random multiple communicationdelays, based on the Lyapunov stability theory, su?cient conditions for theexistence of an observer-based feedback controller are derived, such that theclosed-loop networked nonlinear system is exponentially stable in the sense of mean square and a prescribed H_∞disturbance-rejection-attenuation perfor-mance is also achieved. And then a linear matrix inequality (LMI) approachfor designing such an observer-based H_∞controller is presented. With thehelp of the LMI solvers, the observer-based H_∞controller can easily be ob-tained by solving a certain convex optimization problem. Finally, a numericalexample is used to demonstrate the e?ectiveness of the proposed method.
引文
[1] Antsaklis P., and Baillieul J. Special Issue on Technology of Networked ControlSystems[J]. IEEE Proc., 2007, 95(1):5–8.
[2] J. P. Hespanha, P. Naghshtabrizi, and Y. Xu. A survey of recent results innetworked control systems[J]. IEEE Proc.,2007,95(1):138–162.
[3] Azimi-Sadjadi B. Stability of networked control systems in the presence ofpacket losses[J]. Proc. Conf. Decision Control, Maui, HI, 2003,676–681.
[4] Garc′?a-Rivera M., Barreiro A. Analysis of networked control systems with dropsand variable delays[J]. Automatica, 2007, 43(12):2054–2059.
[5] Goodwin G. C., Haimovich H., Quevedo D. E., Welsh J. S. A moving horizonapproach to networked control system design[J]. IEEE Trans. Autom. Control,2004, 49(9):1427–1445.
[6] Jiang X., Han Q. L., Liu S., Xue A. A new H∞stabilization criterion fornetworked control systems[J]. IEEE Trans. Autom. Control., 2008, 53(4):1025–1032.
[7] Tang B., Liu G. P., Gui W. H. Improvement of state feedback controller designfor networked control systems[J]. IEEE Trans. Circuits Syst. II, Exp. Briefs,2008, 55(5):464–468.
[8] Vatanski N., Georges J. P., Aubrun C., Rondeau E., Ja¨msa¨-Jounela S. L. Net-worked control with delay measurement and estimation[J]. Control Eng. Prac-tice, 2009, 17(2):231–244.
[9] Wang Y., Ding S. X., Ye H., Wang G. A new fault detection scheme for net-worked control systems subject to uncertain time-varying delay[J]. IEEE Trans.Signal Process, 2008, 56(10):5258–5268.
[10] Yue D., Han Q. L., Peng C. State feedback controller design of networkedcontrol systems[J]. IEEE Trans. Circuits Syst. II, Exp. Briefs, 2004, 51(11):640–644.
[11] Yue D., Han Q. L., Lam J. Network-based robust H∞control of systems withuncertainty[J]. Automatica, 2005, 41(6):999–1007.
[12]郭亚峰,李少远.网络控制系统H∞状态反馈控制器设计[J].控制理论与应用, 2008,25(3):414–420.
[13]曲铁军,马克茂,田自耘.离散时间非线性系统的观测器设计[J].电机与控制学报, 2005,9(5):469–472.
[14]刘艳红,李春文,王玉振,吴热冰,楚冰. Lipschitz广义非线性系统观测器设计[J].控制理论与应用, 2007,24(2):205–209.
[15]唐功友,高德欣,张宝琳.基于观测器的受扰非线性系统近似最优跟踪控制[J].控制理论与应用, 2007,24(5):725–472.
[17]明廷涛,张永祥,孙云岭,张西勇. Lipschitz非线性系统状态观测器设计新方法[J].海军工程大学学报, 2008,20(3):104–108.
[17] Liu Y., Wang Z., Liang J., Liu X. Synchronization and State Estimation forDiscrete-Time Complex Networks With Distributed Delays[J]. IEEE Trans.Syst., Man, Cybern. B Cybernetics, 2008,38(5):1314–1325.
[18] Lin W., Ma H. Synchronization Between Adaptively Coupled Systems WithDiscrete and Distributed Time-Delays [J]. IEEE Trans. Autom. Control,2010,55(4):819–830.
[19]白涛.网络化控制系统性能分析与调度优化.上海交通大学博士论文, 2005,2–3.
[20]贲小进.网络控制系统及其在水电站的应用河海大学硕士论文, 2006, 6–7.
[21]黄海.网络控制系统实验平台建设与算法设计.浙江大学博士论文, 2007, 4–6.
[22]王艳.网络控制系统的控制与调度研究.南京理工大学博士论文, 2006, 2–3.
[23]孙海义.网络控制系统的稳定性及H∞控制.东北大学硕士论文, 2006, 24–26.
[24]党向东,张庆灵.多包传输网络控制系统的稳定性[J].渤海大学学报,2008,29(4):380–384.
[25]孙海燕,侯朝桢.具有数据包丢失及多包传输的网络控制系统稳定性[J].控制与决策, 2005,20(4):5110–515.
[26]雷必成,蒋天发,王万良,李祖欣.多包传输网络控制系统的H∞控制器设计[J].武汉理工大学学报, 2007,31(4):692–695.
[27]张玉泉,钟秋海.网络化控制系统中的多包传输[J].微计算机信息, 2009,25(4-1):5–6.
[28]王俊松.复杂网络化系统的分析与综合.天津大学博士论文,2008,2–4.
[29] Wang Z., Ho D. W. C., Liu X. Variance-constrained filtering for uncertainstochastic systems with missing measurements[J]. IEEE Trans. Autom. Control,2003, 48(7):1254–1258.
[30] Wang Z.,Yang F., Ho D. W. C.,Liu X. Robust finite-horizon filtering forstochastic systems with missing measurements[J]. IEEE Trans. Signal Process.Lett., 2005,12(6):437–440.
[31] Wang Z.,Yang F., Ho D. W. C. Robust H∞filtering for stochastic time-delaysystems with missing measurements[J]. IEEE Trans. Signal Process., 2006,54(7):2579–2587.
[32] Shen B., Wang Z., Shu H., and Wei G. On nonlinear H∞filtering for discrete-time stochastic systems with missing measurements[J]. IEEE Trans. Autom.Control, 2008, 53(9):2170–2180.
[33] Sahebsara M., Chen T., Shaha S. L. Optimal H2 filtering in networked controlsystems with multiple packet dropouts[J]. IEEE Trans. Autom. Control, 2007,52(8):1508–1513.
[34] Sahebsara M., Chen T., Shaha S. L. Optimal H∞filtering in networked controlsystems with multiple packet dropouts[J]. Syst. Control Lett., 2008, 57(9):696–702.
[35] Wang Z., Liu X., Yang F., Ho D. W. C., Liu X. Robust H∞control for net-worked systems with random packet losses[J]. IEEE Trans. Syst., Man, Cybern.B Cybernetics, 2007, 37(4):916–924.
[36] Yang F., Wang Z., Hung Y.S., and Gani M. H∞control for networked sys-tems with random communication delays[J]. IEEE Transactions on AutomaticControl,2006,51(3):511–518.
[37]谢德晓,韩笑冬,黄鹤,王执铨.具有时延和丢包的网络控制系统H∞状态反馈控制[J].控制与决策, 2009,24(4):587–592.
[38]杨春曦,关治洪,黄剑.马尔可夫时滞网络控制系统的稳定性[J].华中科技大学学报, 2009,37(3):86–89.
[39]刘丽丽,张庆灵,杜昭平.具有时延和数据包丢失的广义网络控制系统的稳定性[J].东北大学学报, 2008,30(3):318–320.
[40]邱占芝,张庆灵.具有数据包丢失的奇异网络控制系统指数稳定性[J].控制与决策, 2009,24(6):837–842.
[41] Hristu-Varsakelisa D., Zhang L. LQG control of networked control systems withaccess constraints and delays[J].Int. J. Control, 2008,81(8):1266–1280.
[42] Gupta V., Hassibi B., Murray M. R. Optimal LQG control across packet-dropping links[J]. Systems & Control Letters.,2007, 56(6):439–446.
[43] Hu S., Zhu Q. Stochastic optimal control and analysis of stability of networkedcontrol systems with long delay[J].Automatica, 2003,39(11):1877–1884.
[44]马长林,张清国.网络化控制系统的随机最优控制[J].清华大学学报,2008,48(S2):1775–1779.
[45] Gao H., Chen T. Network-based H∞output tracking control[J]. IEEE Trans.Autom. Control, 2008, 53(3):655–667.
[46] Wang Y.L. and Yang G.H. Output tracking control for networked control sys-tems with time delay and packet dropout[J]. Int. J. Control,2008,81(11):1709–1719.
[47] Schenato L. Optimal estimation in networked control systems subject to ran-dom delay and packet drop[J]. IEEE Trans. Autom. Control, 2008, 53(5):1311–1317.
[48] Liu G. P., XiaY. , Rees D., Hu W. Design and stability criteria of networkedpredictive control systems with random network delay in the feedback chan-nel[J]. IEEE Trans. Syst. Man Cybern. C, 2007, 37(2):173–184.
[49] Liu G. P., Xia Y., Chen J., Rees D., Hu W. Networked predictive control ofsystems with random network delays in both forward and feedback channels[J].IEEE Trans. Ind. Electron., 2007,54(3):1282–1297.
[50] Hu W, Liu G. P., Rees D. Event-driven networked predictive control[J]. IEEETrans. Ind. Electron.,2007, 54(3):1603–1613.
[51] Zhao Y. B., Liu G. P., Rees D. Networked predictive control systems based onthe Hammerstein model[J]. IEEE Trans. Circuits Syst. II, Exp. Briefs, 2008,55(5):469–473.
[52] Zhao Y. B., Liu G. P., Rees D. A predictive control-based approach to net-worked Hammerstein systems: design and stability analysis[J]. IEEE Trans.IEEE Trans. Syst. Man Cybern. B Cybernetics, 2008,38(3):700–708.
[53]郑大钟.线性系统理论.清华大学出版社, 2002, 138–139.
[54]俞立.鲁棒控制-线性矩阵不等式处理方法.清华大学出版社, 2002, 7–9.
[55]邱占芝.广义网络控制系统分析、建模与控制.东北大学博士论文, 2006,101–102.
[56] Nahi N. Optimal recursive estimation with uncertain observation[J]. IEEETrans. Inf. Theory, 1969,
[57] Ishii H. H∞control with limited communication and message losses[J]. Syst.Control Lett., 2008, 57(4);322–331.
[58] Sinopoli B., Schenato L., Franceschetti M., Poolla K., Jordan M. I., SastryS. S. Kalman filtering with intermittent observations[J]. IEEE Trans. Autom.Control, 2004, 49(9):1453–1464.
[59] Seiler P., Sengupta R. An H∞approach to networked control[J]. IEEE Trans.Autom. Control, 2005., 50(3):356–364.
[60] Wu J., Chen T. Design of networked control systems with packet dropouts[J].IEEE Trans. Autom. Control, 2007, 52(7):1314–1319.
[61] Zhang W. A., Yu L. Output feedback stabilization of networked control systemswith packet dropouts[J]. IEEE Trans. Autom. Control, 2007, 52(9):1705–1710.
[62] Yu M., Wang L., Chu T., Xie G. Modelling and control of networked systemsvia jump system approach[J]. IET Control Theory Appl., 2008., 2(6):535–541.
[63] Savkin A. V., Petersen I. R. Robust filtering with missing data and a determin-istic description of noise and uncertainty[J]. Int. J. Syst. Sci., 1997, 28(4):373–390.
[64] Savkin A. V., Petersen I. R., Moheimani S. O. R. Model validation andstate estimation for uncertain continuous-time systems with missing discrete-continuous data[J]. Comput. Electr. Eng., 1999, 25(1):29–43.
[65] Cao J., Zhong S., Hu Y. Novel delay-dependent stability conditions for a class ofMIMO networked control systems with nonlinear perturbation[J]. Appl. Math.Comput., 2008, 197(2):797–809.
[66] Jiang X., Han Q. L. On designing fuzzy controllers for a class of nonlinearnetworked control systems[J]. IEEE Trans. Fuzzy Syst., 2008, 16(4):1050–1060.
[67] Polushin I. G., Liu P. X., Lung C. H. On the model-based approach to nonlinearnetworked control systems[J]. Automatica, 2008, 44(9):2409–2414.
[68] Walsh G. C., Beldiman O., Bushnell L. G. Asymptotic behavior of nonlinearnetworked control systems[J]. IEEE Trans. Autom. Control, 2001, 46(7):1093–1097.
[69] Yu M., Wang L., Chu T. Sampled-data stabilisation of networked control sys-tems with nonlinearity[J]. IEE Proc. Control Theory. Appl., 2005, 152(4):609–614.
[70] Yue D., Lam J., Wang Z. Persistent disturbance rejection via state feedback fornetworked control systems[J]. Chaos, Solitons & Fractals, 2009, 40(1):382–391.
[71] Zhang X., Lu G., Zheng Y. Stabilization of networked stochastic time-delayfuzzy systems with data dropout[J]. IEEE Trans. Fuzzy Syst., 2008, 16(3):798–807.
[72] Savkin A. V., Cheng T. M. Detectability and output feedback stabilizability ofnonlinear networked control systems[J]. IEEE Trans. Autom. Control., 2007,52(4):730–735. IT-15, (4):457–462.
[73] Ho D. W. C., Lu G. Robust stabilization for a class of discrete-time non-linearsystems via output feedback: The unified LMI approach[J]. Int. J. Control,2003, 76(2):105–115.
[74] Hong S. H. Scheduling algorithm of data sampling times in the integrated com-munication and control systems[J]. IEEE Trans. Control Syst. Technol., 1995,3(2):225–230.
[75] Boyd S., Ghaoui L. E., Feron E., Balakrishnan V. Linear Matrix Inequalities inSystem and Control Theory. Philadelphia, PA: SIAM Stud. Appl. Math., 1994.
[76] Yakubovich V. A. The S-procedure in nonlinear control theory[J]. VestnikLeningrad Univ. Math., 1977, 4:73–93.
[77] Tarn T. J., Rasis Y. Observers for nonlinear stochastic systems[J]. IEEE Trans.Autom. Control, 1976, AC-21, (4):441–448.
[78] Bouhtouri A. E., Hinrichsen D., Pritchard A.J. H∞-type control for discrete-time stochastic systems[J]. Int. J. Robust Nonlinear Control, 1999, 9(13):923–948.
[79]白涛,吴智铭,杨根科.网络化的控制系统[J].控制理论与应用,2004,21(4):584–590.
[80]赵伟平.有时延和数据包丢失的网络系统的稳定化控制.西安电子科技大学硕士论文,2008,5–6.
[81]张勇.大时滞网络控制系统分析与设计的研究.中国海洋大学博士论文,2008,9–12.
[82]刘明.线性网络控制系统稳定性分析与控制器设计.东北大学硕士论文,2006,2–2.
[83]王书喜.网络控制系统仿真方法的研究.西安理工大学硕士论文,2007,10–12.
[84] Gao H., Chen T., Lam J. A new delay system approach to network-basedcontrol[J]. Automatica, 2008, 44(1):39–52.
[85] Gao H., Meng X., Chen T. Stabilization of networked control systems with anew delay characterization[J]. IEEE Trans. Autom. Control, 2008, 53(9):2142–2148.
[86]李静,史建国,左斌.具有参数不确定性的长时延网络控制系统研究[J].系统仿真学报, 2009,21(12):3684–3688.
[87] Huang D., Nguang S. K. State feedback control of uncertain networkedcontrol systems with random time delays[J]. IEEE Trans. Autom. Control,2008,53(3):829–834.
[88]刘磊明,童朝南,武延坤一种带有动态输出反馈控制器的网络控制系统的Markov跳变模型[J].自动化学报, 2009,35(5):627–631.
[89] Zhang L., Shi Y., Chen T., Huang B. A new method for stabilization of net-worked control systems with random delays[J]. IEEE Trans. Autom. Control,2005, 50(8):1177–1181.
[90] Zhang W. A., Yu L. A robust control approach to stabilization of networked con-trol systems with time-varying delays[J]. Automatica, 2009,45(10):2440–2445.
[91] Deng M. and Inoue A. Networked non-linear control for an aluminum platethermal process with timedelays[J]. Int. J. Syst. Sci.,2008,39(11):1075–1080.
[92]刘丽丽,张庆灵.非线性的实时网络控制系统稳定性分析[J].东北大学学报,2008,29(3):305–307.
[93] Ray A. Output feedback control under randomly varying distributed delays[J].Journal of Guidance, Control and Dynamic,1994,17(4):701–711.
[94] Wang Z. and Yang F. Robust filtering for uncertain linear systems with delayedstates and outputs[J]. IEEE Trans. Circuits Syst. I,2002,49(1):125–130.
[95] Yaz E. and Ray A. Linear unbiased state estimation for random models withsensor delay[J]. Proc. Conf. Decision and Control, Kobe, Japan, 1996,47–52.
[96] Hounkpevi, F. O., Yaz, E. E. Robust minimum variance linear state esti-mators for multiple sensors with di?erent failure rates[J]. Automatica, 2007,43(7):1274–1280.
[97] Wei G., Wang Z. and Shu H. Robust filtering with stochastic nonlinearities andmultiple missing measurements[J]. Automatica, 2009, 45(3):836–841.
[98] Hounkpevi, F. O., Yaz, E. E. Minimum variance generalized state estima-tors for multiple sensors with di?erent delay rates[J]. Signal Processing, 2007,87(4):602–613.
[2] J. P. Hespanha, P. Naghshtabrizi, and Y. Xu. A survey of recent results innetworked control systems[J]. IEEE Proc.,2007,95(1):138–162.
[3] Azimi-Sadjadi B. Stability of networked control systems in the presence ofpacket losses[J]. Proc. Conf. Decision Control, Maui, HI, 2003,676–681.
[4] Garc′?a-Rivera M., Barreiro A. Analysis of networked control systems with dropsand variable delays[J]. Automatica, 2007, 43(12):2054–2059.
[5] Goodwin G. C., Haimovich H., Quevedo D. E., Welsh J. S. A moving horizonapproach to networked control system design[J]. IEEE Trans. Autom. Control,2004, 49(9):1427–1445.
[6] Jiang X., Han Q. L., Liu S., Xue A. A new H∞stabilization criterion fornetworked control systems[J]. IEEE Trans. Autom. Control., 2008, 53(4):1025–1032.
[7] Tang B., Liu G. P., Gui W. H. Improvement of state feedback controller designfor networked control systems[J]. IEEE Trans. Circuits Syst. II, Exp. Briefs,2008, 55(5):464–468.
[8] Vatanski N., Georges J. P., Aubrun C., Rondeau E., Ja¨msa¨-Jounela S. L. Net-worked control with delay measurement and estimation[J]. Control Eng. Prac-tice, 2009, 17(2):231–244.
[9] Wang Y., Ding S. X., Ye H., Wang G. A new fault detection scheme for net-worked control systems subject to uncertain time-varying delay[J]. IEEE Trans.Signal Process, 2008, 56(10):5258–5268.
[10] Yue D., Han Q. L., Peng C. State feedback controller design of networkedcontrol systems[J]. IEEE Trans. Circuits Syst. II, Exp. Briefs, 2004, 51(11):640–644.
[11] Yue D., Han Q. L., Lam J. Network-based robust H∞control of systems withuncertainty[J]. Automatica, 2005, 41(6):999–1007.
[12]郭亚峰,李少远.网络控制系统H∞状态反馈控制器设计[J].控制理论与应用, 2008,25(3):414–420.
[13]曲铁军,马克茂,田自耘.离散时间非线性系统的观测器设计[J].电机与控制学报, 2005,9(5):469–472.
[14]刘艳红,李春文,王玉振,吴热冰,楚冰. Lipschitz广义非线性系统观测器设计[J].控制理论与应用, 2007,24(2):205–209.
[15]唐功友,高德欣,张宝琳.基于观测器的受扰非线性系统近似最优跟踪控制[J].控制理论与应用, 2007,24(5):725–472.
[17]明廷涛,张永祥,孙云岭,张西勇. Lipschitz非线性系统状态观测器设计新方法[J].海军工程大学学报, 2008,20(3):104–108.
[17] Liu Y., Wang Z., Liang J., Liu X. Synchronization and State Estimation forDiscrete-Time Complex Networks With Distributed Delays[J]. IEEE Trans.Syst., Man, Cybern. B Cybernetics, 2008,38(5):1314–1325.
[18] Lin W., Ma H. Synchronization Between Adaptively Coupled Systems WithDiscrete and Distributed Time-Delays [J]. IEEE Trans. Autom. Control,2010,55(4):819–830.
[19]白涛.网络化控制系统性能分析与调度优化.上海交通大学博士论文, 2005,2–3.
[20]贲小进.网络控制系统及其在水电站的应用河海大学硕士论文, 2006, 6–7.
[21]黄海.网络控制系统实验平台建设与算法设计.浙江大学博士论文, 2007, 4–6.
[22]王艳.网络控制系统的控制与调度研究.南京理工大学博士论文, 2006, 2–3.
[23]孙海义.网络控制系统的稳定性及H∞控制.东北大学硕士论文, 2006, 24–26.
[24]党向东,张庆灵.多包传输网络控制系统的稳定性[J].渤海大学学报,2008,29(4):380–384.
[25]孙海燕,侯朝桢.具有数据包丢失及多包传输的网络控制系统稳定性[J].控制与决策, 2005,20(4):5110–515.
[26]雷必成,蒋天发,王万良,李祖欣.多包传输网络控制系统的H∞控制器设计[J].武汉理工大学学报, 2007,31(4):692–695.
[27]张玉泉,钟秋海.网络化控制系统中的多包传输[J].微计算机信息, 2009,25(4-1):5–6.
[28]王俊松.复杂网络化系统的分析与综合.天津大学博士论文,2008,2–4.
[29] Wang Z., Ho D. W. C., Liu X. Variance-constrained filtering for uncertainstochastic systems with missing measurements[J]. IEEE Trans. Autom. Control,2003, 48(7):1254–1258.
[30] Wang Z.,Yang F., Ho D. W. C.,Liu X. Robust finite-horizon filtering forstochastic systems with missing measurements[J]. IEEE Trans. Signal Process.Lett., 2005,12(6):437–440.
[31] Wang Z.,Yang F., Ho D. W. C. Robust H∞filtering for stochastic time-delaysystems with missing measurements[J]. IEEE Trans. Signal Process., 2006,54(7):2579–2587.
[32] Shen B., Wang Z., Shu H., and Wei G. On nonlinear H∞filtering for discrete-time stochastic systems with missing measurements[J]. IEEE Trans. Autom.Control, 2008, 53(9):2170–2180.
[33] Sahebsara M., Chen T., Shaha S. L. Optimal H2 filtering in networked controlsystems with multiple packet dropouts[J]. IEEE Trans. Autom. Control, 2007,52(8):1508–1513.
[34] Sahebsara M., Chen T., Shaha S. L. Optimal H∞filtering in networked controlsystems with multiple packet dropouts[J]. Syst. Control Lett., 2008, 57(9):696–702.
[35] Wang Z., Liu X., Yang F., Ho D. W. C., Liu X. Robust H∞control for net-worked systems with random packet losses[J]. IEEE Trans. Syst., Man, Cybern.B Cybernetics, 2007, 37(4):916–924.
[36] Yang F., Wang Z., Hung Y.S., and Gani M. H∞control for networked sys-tems with random communication delays[J]. IEEE Transactions on AutomaticControl,2006,51(3):511–518.
[37]谢德晓,韩笑冬,黄鹤,王执铨.具有时延和丢包的网络控制系统H∞状态反馈控制[J].控制与决策, 2009,24(4):587–592.
[38]杨春曦,关治洪,黄剑.马尔可夫时滞网络控制系统的稳定性[J].华中科技大学学报, 2009,37(3):86–89.
[39]刘丽丽,张庆灵,杜昭平.具有时延和数据包丢失的广义网络控制系统的稳定性[J].东北大学学报, 2008,30(3):318–320.
[40]邱占芝,张庆灵.具有数据包丢失的奇异网络控制系统指数稳定性[J].控制与决策, 2009,24(6):837–842.
[41] Hristu-Varsakelisa D., Zhang L. LQG control of networked control systems withaccess constraints and delays[J].Int. J. Control, 2008,81(8):1266–1280.
[42] Gupta V., Hassibi B., Murray M. R. Optimal LQG control across packet-dropping links[J]. Systems & Control Letters.,2007, 56(6):439–446.
[43] Hu S., Zhu Q. Stochastic optimal control and analysis of stability of networkedcontrol systems with long delay[J].Automatica, 2003,39(11):1877–1884.
[44]马长林,张清国.网络化控制系统的随机最优控制[J].清华大学学报,2008,48(S2):1775–1779.
[45] Gao H., Chen T. Network-based H∞output tracking control[J]. IEEE Trans.Autom. Control, 2008, 53(3):655–667.
[46] Wang Y.L. and Yang G.H. Output tracking control for networked control sys-tems with time delay and packet dropout[J]. Int. J. Control,2008,81(11):1709–1719.
[47] Schenato L. Optimal estimation in networked control systems subject to ran-dom delay and packet drop[J]. IEEE Trans. Autom. Control, 2008, 53(5):1311–1317.
[48] Liu G. P., XiaY. , Rees D., Hu W. Design and stability criteria of networkedpredictive control systems with random network delay in the feedback chan-nel[J]. IEEE Trans. Syst. Man Cybern. C, 2007, 37(2):173–184.
[49] Liu G. P., Xia Y., Chen J., Rees D., Hu W. Networked predictive control ofsystems with random network delays in both forward and feedback channels[J].IEEE Trans. Ind. Electron., 2007,54(3):1282–1297.
[50] Hu W, Liu G. P., Rees D. Event-driven networked predictive control[J]. IEEETrans. Ind. Electron.,2007, 54(3):1603–1613.
[51] Zhao Y. B., Liu G. P., Rees D. Networked predictive control systems based onthe Hammerstein model[J]. IEEE Trans. Circuits Syst. II, Exp. Briefs, 2008,55(5):469–473.
[52] Zhao Y. B., Liu G. P., Rees D. A predictive control-based approach to net-worked Hammerstein systems: design and stability analysis[J]. IEEE Trans.IEEE Trans. Syst. Man Cybern. B Cybernetics, 2008,38(3):700–708.
[53]郑大钟.线性系统理论.清华大学出版社, 2002, 138–139.
[54]俞立.鲁棒控制-线性矩阵不等式处理方法.清华大学出版社, 2002, 7–9.
[55]邱占芝.广义网络控制系统分析、建模与控制.东北大学博士论文, 2006,101–102.
[56] Nahi N. Optimal recursive estimation with uncertain observation[J]. IEEETrans. Inf. Theory, 1969,
[57] Ishii H. H∞control with limited communication and message losses[J]. Syst.Control Lett., 2008, 57(4);322–331.
[58] Sinopoli B., Schenato L., Franceschetti M., Poolla K., Jordan M. I., SastryS. S. Kalman filtering with intermittent observations[J]. IEEE Trans. Autom.Control, 2004, 49(9):1453–1464.
[59] Seiler P., Sengupta R. An H∞approach to networked control[J]. IEEE Trans.Autom. Control, 2005., 50(3):356–364.
[60] Wu J., Chen T. Design of networked control systems with packet dropouts[J].IEEE Trans. Autom. Control, 2007, 52(7):1314–1319.
[61] Zhang W. A., Yu L. Output feedback stabilization of networked control systemswith packet dropouts[J]. IEEE Trans. Autom. Control, 2007, 52(9):1705–1710.
[62] Yu M., Wang L., Chu T., Xie G. Modelling and control of networked systemsvia jump system approach[J]. IET Control Theory Appl., 2008., 2(6):535–541.
[63] Savkin A. V., Petersen I. R. Robust filtering with missing data and a determin-istic description of noise and uncertainty[J]. Int. J. Syst. Sci., 1997, 28(4):373–390.
[64] Savkin A. V., Petersen I. R., Moheimani S. O. R. Model validation andstate estimation for uncertain continuous-time systems with missing discrete-continuous data[J]. Comput. Electr. Eng., 1999, 25(1):29–43.
[65] Cao J., Zhong S., Hu Y. Novel delay-dependent stability conditions for a class ofMIMO networked control systems with nonlinear perturbation[J]. Appl. Math.Comput., 2008, 197(2):797–809.
[66] Jiang X., Han Q. L. On designing fuzzy controllers for a class of nonlinearnetworked control systems[J]. IEEE Trans. Fuzzy Syst., 2008, 16(4):1050–1060.
[67] Polushin I. G., Liu P. X., Lung C. H. On the model-based approach to nonlinearnetworked control systems[J]. Automatica, 2008, 44(9):2409–2414.
[68] Walsh G. C., Beldiman O., Bushnell L. G. Asymptotic behavior of nonlinearnetworked control systems[J]. IEEE Trans. Autom. Control, 2001, 46(7):1093–1097.
[69] Yu M., Wang L., Chu T. Sampled-data stabilisation of networked control sys-tems with nonlinearity[J]. IEE Proc. Control Theory. Appl., 2005, 152(4):609–614.
[70] Yue D., Lam J., Wang Z. Persistent disturbance rejection via state feedback fornetworked control systems[J]. Chaos, Solitons & Fractals, 2009, 40(1):382–391.
[71] Zhang X., Lu G., Zheng Y. Stabilization of networked stochastic time-delayfuzzy systems with data dropout[J]. IEEE Trans. Fuzzy Syst., 2008, 16(3):798–807.
[72] Savkin A. V., Cheng T. M. Detectability and output feedback stabilizability ofnonlinear networked control systems[J]. IEEE Trans. Autom. Control., 2007,52(4):730–735. IT-15, (4):457–462.
[73] Ho D. W. C., Lu G. Robust stabilization for a class of discrete-time non-linearsystems via output feedback: The unified LMI approach[J]. Int. J. Control,2003, 76(2):105–115.
[74] Hong S. H. Scheduling algorithm of data sampling times in the integrated com-munication and control systems[J]. IEEE Trans. Control Syst. Technol., 1995,3(2):225–230.
[75] Boyd S., Ghaoui L. E., Feron E., Balakrishnan V. Linear Matrix Inequalities inSystem and Control Theory. Philadelphia, PA: SIAM Stud. Appl. Math., 1994.
[76] Yakubovich V. A. The S-procedure in nonlinear control theory[J]. VestnikLeningrad Univ. Math., 1977, 4:73–93.
[77] Tarn T. J., Rasis Y. Observers for nonlinear stochastic systems[J]. IEEE Trans.Autom. Control, 1976, AC-21, (4):441–448.
[78] Bouhtouri A. E., Hinrichsen D., Pritchard A.J. H∞-type control for discrete-time stochastic systems[J]. Int. J. Robust Nonlinear Control, 1999, 9(13):923–948.
[79]白涛,吴智铭,杨根科.网络化的控制系统[J].控制理论与应用,2004,21(4):584–590.
[80]赵伟平.有时延和数据包丢失的网络系统的稳定化控制.西安电子科技大学硕士论文,2008,5–6.
[81]张勇.大时滞网络控制系统分析与设计的研究.中国海洋大学博士论文,2008,9–12.
[82]刘明.线性网络控制系统稳定性分析与控制器设计.东北大学硕士论文,2006,2–2.
[83]王书喜.网络控制系统仿真方法的研究.西安理工大学硕士论文,2007,10–12.
[84] Gao H., Chen T., Lam J. A new delay system approach to network-basedcontrol[J]. Automatica, 2008, 44(1):39–52.
[85] Gao H., Meng X., Chen T. Stabilization of networked control systems with anew delay characterization[J]. IEEE Trans. Autom. Control, 2008, 53(9):2142–2148.
[86]李静,史建国,左斌.具有参数不确定性的长时延网络控制系统研究[J].系统仿真学报, 2009,21(12):3684–3688.
[87] Huang D., Nguang S. K. State feedback control of uncertain networkedcontrol systems with random time delays[J]. IEEE Trans. Autom. Control,2008,53(3):829–834.
[88]刘磊明,童朝南,武延坤一种带有动态输出反馈控制器的网络控制系统的Markov跳变模型[J].自动化学报, 2009,35(5):627–631.
[89] Zhang L., Shi Y., Chen T., Huang B. A new method for stabilization of net-worked control systems with random delays[J]. IEEE Trans. Autom. Control,2005, 50(8):1177–1181.
[90] Zhang W. A., Yu L. A robust control approach to stabilization of networked con-trol systems with time-varying delays[J]. Automatica, 2009,45(10):2440–2445.
[91] Deng M. and Inoue A. Networked non-linear control for an aluminum platethermal process with timedelays[J]. Int. J. Syst. Sci.,2008,39(11):1075–1080.
[92]刘丽丽,张庆灵.非线性的实时网络控制系统稳定性分析[J].东北大学学报,2008,29(3):305–307.
[93] Ray A. Output feedback control under randomly varying distributed delays[J].Journal of Guidance, Control and Dynamic,1994,17(4):701–711.
[94] Wang Z. and Yang F. Robust filtering for uncertain linear systems with delayedstates and outputs[J]. IEEE Trans. Circuits Syst. I,2002,49(1):125–130.
[95] Yaz E. and Ray A. Linear unbiased state estimation for random models withsensor delay[J]. Proc. Conf. Decision and Control, Kobe, Japan, 1996,47–52.
[96] Hounkpevi, F. O., Yaz, E. E. Robust minimum variance linear state esti-mators for multiple sensors with di?erent failure rates[J]. Automatica, 2007,43(7):1274–1280.
[97] Wei G., Wang Z. and Shu H. Robust filtering with stochastic nonlinearities andmultiple missing measurements[J]. Automatica, 2009, 45(3):836–841.
[98] Hounkpevi, F. O., Yaz, E. E. Minimum variance generalized state estima-tors for multiple sensors with di?erent delay rates[J]. Signal Processing, 2007,87(4):602–613.