网络控制系统时延补偿及变采样周期调度方法
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摘要
网络控制系统是随着自动控制技术、网络通信技术、计算机信息技术的飞速发展而出现的一种新型的分布式、智能化、网络化实时反馈控制系统,以其交互性好、易于扩展和维护、可靠性高、资源共享等优点,在远程遥控操作、无线网络机器人、汽车、高速动车、兵器系统、航空航天领域,以及基于现场总线及以太网的工业控制系统等诸多领域具有广泛的应用前景。因此,对网络控制系统的相关问题进行研究是当前控制理论领域研究的热点,具有重要意义。
网络的介入不可避免地在控制系统中引起网络诱导时延、数据包丢失等问题,使得传统控制系统的研究方法难以直接应用于网络控制系统,迫切需要研究现有的控制方法怎样才能应用于网络控制系统中,以及探索研究新的基于网络的控制理论与方法。同时,受网络带宽资源有限的限制,如何采用合适的调度方法合理分配网络资源对提高网络利用率以及控制系统的性能也至关重要。因此,网络控制系统的性能不仅取决于控制策略的优劣,同时还依赖于网络中信息调度策略的优劣,两者是相关联的、缺一不可的。为此,本文主要进行了如下几方面的研究：
1.针对网络控制系统具有随机不确定时延的特点,通过对大量实测网络时延数据样本的分析,提出了网络时延的自适应AR预测模型。该模型在兼顾算法的预测精度和实时性的基础上,确定了模型的阶数,并利用最小均方算法根据新的时延值在线调整模型的加权系数,进而通过建立的模型对网络时延进行预测。仿真实验表明基于参数自校正AR模型的时延估计算法对时延有很好的预测效果。
2.针对传统广义预测控制对时延补偿实时性差,提出了一种对网络长时延补偿的改进广义预测控制算法。该算法根据时延的估计值来确定合适的预测步长及控制时域,避免了求解Diophantine方程等复杂计算,降低在线计算量。仿真实验表明该方法对网络时延具有很好的补偿效果,有很好的实时性,对干扰和丢包具有良好的鲁棒性。同时提出了一种容易实现反馈控制的长时延状态观测器,实现了极点的任意配置,仿真实验表明该方法保证了系统响应的快速性和稳定性。
3.针对变采样周期对系统控制性能的影响,分析确定了NCS采样周期的受限条件,提出了一种递推式变采样周期在线动态调度算法,可根据系统输出与均值的偏差、方差以及系统输出振荡情况来在线调节系统的采样周期,以绝对误差积分指标IAE等来衡量控制回路性能,仿真实验表明基于递推式变采样周期调度算法有效地改善了网络控制系统的控制性能,保证了系统的稳定性。
4.针对网络控制系统中网络带宽有限等问题,考虑系统误差、误差变化率和网络利用率等因素,提出了一种模糊动态反馈变采样周期调度算法。该方法可根据系统误差及误差变化率运用模糊推理的方法来确定回路的优先级。通过网络利用率及控制性能指标来求取网络控制系统中各个回路的采样周期,合理地分配了网络有限带宽资源。仿真实验表明该方法提高了系统的控制性能,改善了网络的服务质量。
With the rapid development of automatic control technology, network communication technology, computer technology and information technology, as a new type of distributed, intelligent, and network-based realtime feedback control system, Networked Control System (NCS) is used widely in remote control operation, wireless netwok robot, automotive, CRH train, certain weapons systems, aerospace, as well as fieldbus and industrial ethernet based industrial control systems and many other areas for the advantages such as low cost, easy to extend and maintain, high efficient, flexible, and resource sharing, and the abroad application foreground. Therefore, some research issues related to NCS are of great significant in the current field of control theory.
The traditional control methods are difficult to be applied directly to NCS for network-induced delay, packet loss and other issues caused by the network intervention in the control system. There is an urgent need to study how to extend the existing control methods to NCS, and explore new control theory and methods based on network. Subject to network bandwidth limitation, at the same time, it is important to allocate reasonably network resource through available scheduling methods in order to improve the utilization of network and the performance of control system. Therefore, the performance of NCS depends not only on the merits of the control strategy, but also on the effectiveness of network scheduling policy, which need to be considered together. Therefore, this dissertation is made and main contributions are concluded as follows:
Firstly, according to the random uncertain time-delay of networked control system, a large number of measured delay sample data is analyzed and treated, then the adaptive AR predictive model is proposed. On the basis of consideration on prediction precision and real-time property in algorithm, the model ascertains its order, and uses the least mean square algorithm based on the new time-delay in order to adjust the weighting factor online. The simulation results show that the delay estimation algorithm based on self-tuning AR model has much better prediction effect on delay.
Secondly, for traditional GPC used to compensate delay is short of real-time property, an improved GPC algorithm is proposed to compensate random long delay of network. The predictive step and control horizon of GPC are determined according to the estimated value of network time delay. The method avoids solving the Diophantine equations in order to reduce the computational quantity. The simulation results show that the method has very good effect on delay compensation, and well real-time property, and good robustness on interference and loss package. A state observer of long time delay is put forward simultaneously, which can realize easily state-feedback control and arbitrary pole configuration. The simulation results show that the method has good effect on delay compensation and good stability.
Thirdly, the constraints of sampling period is analyzed and determined, and an online dynamic scheduling algorithm with recursive and variable sampling period is put forward, considering the impact of variable sampling period to network control performance. It can adjust the sampling period according to the mean, variance and oscillation of system output. It reflects the QoC of NCS through error absolute integral index IAE. The simulation results show that the scheduling algorithm effectively improve the control performance and the stability of system.
Finally, subject to network bandwidth limitation in NCS, a fuzzy dynamic feedback scheduling algorithm of varying sampling period is proposed, by considering the error, error rate and network utilization. It uses the fuzzy inference method to determine the priorities of loops according to the error and error rate, and uses the network utilization and control performance index to determine the sampling period of each loop in NCS, so it distributes reasonably network limited bandwidth resources. The simulation results show that the method can improve the performance of NCS, and improve the quality of network service.
网络的介入不可避免地在控制系统中引起网络诱导时延、数据包丢失等问题,使得传统控制系统的研究方法难以直接应用于网络控制系统,迫切需要研究现有的控制方法怎样才能应用于网络控制系统中,以及探索研究新的基于网络的控制理论与方法。同时,受网络带宽资源有限的限制,如何采用合适的调度方法合理分配网络资源对提高网络利用率以及控制系统的性能也至关重要。因此,网络控制系统的性能不仅取决于控制策略的优劣,同时还依赖于网络中信息调度策略的优劣,两者是相关联的、缺一不可的。为此,本文主要进行了如下几方面的研究：
1.针对网络控制系统具有随机不确定时延的特点,通过对大量实测网络时延数据样本的分析,提出了网络时延的自适应AR预测模型。该模型在兼顾算法的预测精度和实时性的基础上,确定了模型的阶数,并利用最小均方算法根据新的时延值在线调整模型的加权系数,进而通过建立的模型对网络时延进行预测。仿真实验表明基于参数自校正AR模型的时延估计算法对时延有很好的预测效果。
2.针对传统广义预测控制对时延补偿实时性差,提出了一种对网络长时延补偿的改进广义预测控制算法。该算法根据时延的估计值来确定合适的预测步长及控制时域,避免了求解Diophantine方程等复杂计算,降低在线计算量。仿真实验表明该方法对网络时延具有很好的补偿效果,有很好的实时性,对干扰和丢包具有良好的鲁棒性。同时提出了一种容易实现反馈控制的长时延状态观测器,实现了极点的任意配置,仿真实验表明该方法保证了系统响应的快速性和稳定性。
3.针对变采样周期对系统控制性能的影响,分析确定了NCS采样周期的受限条件,提出了一种递推式变采样周期在线动态调度算法,可根据系统输出与均值的偏差、方差以及系统输出振荡情况来在线调节系统的采样周期,以绝对误差积分指标IAE等来衡量控制回路性能,仿真实验表明基于递推式变采样周期调度算法有效地改善了网络控制系统的控制性能,保证了系统的稳定性。
4.针对网络控制系统中网络带宽有限等问题,考虑系统误差、误差变化率和网络利用率等因素,提出了一种模糊动态反馈变采样周期调度算法。该方法可根据系统误差及误差变化率运用模糊推理的方法来确定回路的优先级。通过网络利用率及控制性能指标来求取网络控制系统中各个回路的采样周期,合理地分配了网络有限带宽资源。仿真实验表明该方法提高了系统的控制性能,改善了网络的服务质量。
With the rapid development of automatic control technology, network communication technology, computer technology and information technology, as a new type of distributed, intelligent, and network-based realtime feedback control system, Networked Control System (NCS) is used widely in remote control operation, wireless netwok robot, automotive, CRH train, certain weapons systems, aerospace, as well as fieldbus and industrial ethernet based industrial control systems and many other areas for the advantages such as low cost, easy to extend and maintain, high efficient, flexible, and resource sharing, and the abroad application foreground. Therefore, some research issues related to NCS are of great significant in the current field of control theory.
The traditional control methods are difficult to be applied directly to NCS for network-induced delay, packet loss and other issues caused by the network intervention in the control system. There is an urgent need to study how to extend the existing control methods to NCS, and explore new control theory and methods based on network. Subject to network bandwidth limitation, at the same time, it is important to allocate reasonably network resource through available scheduling methods in order to improve the utilization of network and the performance of control system. Therefore, the performance of NCS depends not only on the merits of the control strategy, but also on the effectiveness of network scheduling policy, which need to be considered together. Therefore, this dissertation is made and main contributions are concluded as follows:
Firstly, according to the random uncertain time-delay of networked control system, a large number of measured delay sample data is analyzed and treated, then the adaptive AR predictive model is proposed. On the basis of consideration on prediction precision and real-time property in algorithm, the model ascertains its order, and uses the least mean square algorithm based on the new time-delay in order to adjust the weighting factor online. The simulation results show that the delay estimation algorithm based on self-tuning AR model has much better prediction effect on delay.
Secondly, for traditional GPC used to compensate delay is short of real-time property, an improved GPC algorithm is proposed to compensate random long delay of network. The predictive step and control horizon of GPC are determined according to the estimated value of network time delay. The method avoids solving the Diophantine equations in order to reduce the computational quantity. The simulation results show that the method has very good effect on delay compensation, and well real-time property, and good robustness on interference and loss package. A state observer of long time delay is put forward simultaneously, which can realize easily state-feedback control and arbitrary pole configuration. The simulation results show that the method has good effect on delay compensation and good stability.
Thirdly, the constraints of sampling period is analyzed and determined, and an online dynamic scheduling algorithm with recursive and variable sampling period is put forward, considering the impact of variable sampling period to network control performance. It can adjust the sampling period according to the mean, variance and oscillation of system output. It reflects the QoC of NCS through error absolute integral index IAE. The simulation results show that the scheduling algorithm effectively improve the control performance and the stability of system.
Finally, subject to network bandwidth limitation in NCS, a fuzzy dynamic feedback scheduling algorithm of varying sampling period is proposed, by considering the error, error rate and network utilization. It uses the fuzzy inference method to determine the priorities of loops according to the error and error rate, and uses the network utilization and control performance index to determine the sampling period of each loop in NCS, so it distributes reasonably network limited bandwidth resources. The simulation results show that the method can improve the performance of NCS, and improve the quality of network service.
引文
[1]Lian F L. Analysis, design, modeling, and control of networked control systems[D]. Michigan: University of Michigan,2001.
[2]Yang T C. Networked control system:a brief survey[C]. Proceedings of IEEE Control Theory and Applications,2006,153(4):403-412.
[3]Park H S, Kim Y H, Kim D S, et al. A scheduling method for network-based control systems[J]. IEEE Transactions on Control Systems Technology,2002,10(3):318-330.
[4]Richard J P. Time-delay systems:an overview of some recent advances and openproblems[J]. Automatica,2003,39(10):1667-1694.
[5]Nilsson J, Bernhardsson B, Wittenmark B. Stochastic analysis and control of real time systems with random time delays [J]. Automatica,1998,34(1):57-64.
[6]Ray A, Halevi Y. Integrated communication and control systems:part Ⅰ-analysis and part Ⅱ-design considerations[J]. Journal of Dynamic Systems,Measurement, and Control.1988,110(4):367-381.
[7]Lian F L, Moyne J, Tilbury D M. Network design consideration for distributed control systems[J]. IEEE Transactions on Control Systems Technology,2002,10(2):297-307.
[8]Ye H. Wireless local area networks in the manufacturing industry[C]. Proceedings of the American Control Conference. Chicago, Illinois,2000:2363-2367.
[9]Nilsson J. Real-time control systems with delays[D]. Sweden:Lund Institute of Technology,1998.
[10]Lawrenz W. CAN system engineering:from theory to practical applications[M]. New York:Springer-Verlag,1997.
[11]马卫国.具有时延和丢包的的鲁棒网络控制系统研究[D].大连：大连理工大学,2008.
[12]Palopoli L, Abeni L, Buttazzo G, et al. Real-time control system analysis:an integrated approach[C]. The 21st IEEE Real-Time Systems Symposium, Orlando, Florida, USA,2000:131-140.
[13]王万良,蒋一波,李祖欣等.网络控制与调度方法及其应用[M].北京：科学技术出版社,2009.
[14]Zhang W. Stability analysis of networked control systems[D]. Cleveland:Case Western Reserve University,2001.
[15]Walsh G C, Ye H. Scheduling of networked control systems[J]. IEEE Control Systems Magazine, 2001,21(1):57-65.
[16]Nillsson J, Bernhardsson B. LQG control over a Markov communication network[C]. Procceeding of the 36th IEEE CDC. San Diego, California,1997:4586-4591.
[17]Lincoln B, Bemhardsson B. Optimal control over networks with long random delays[C]. Proceedings of the international symposium on mathematical theory of networks and systems,2000:84-90.
[18]朱其新,胡寿松,侯霞.长时滞网络控制系统随机稳定性研究[J].东南大学学报(自然科学版),2003,33(3)：368-371.
[19]朱其新,胡寿松.网络控制系统的分析与建模[J].信息与控制,2003,32(1)：5-8,13.
[20]Ma C L, Fang H J. Stochastic stabilization analysis of networked control systems[J]. Journal of SystemsEngineering and Eleetronic,2007,18(1):137-141.
[21]Hu S S, Zhu Q X. Stochastic optimal control and analysis of stability of networked control systems with long delay. Automatica,2003,39(11):1877-1884.
[22]杨业,王永骥,徐建省.输出反馈网络控制系统的随机时滞补偿.华中科技大学学报(自然科学版),2006,34(5)：95-98.
[23]朱其新,胡寿松.网络控制系统的随机输出反馈控制[J].应用科学学报,2004,22(1)：71-75.
[24]白涛,吴智铭,杨根科.网络化控制系统中的抖动优化调度算法[J].控制与决策,2004,19(4)：397-401.
[25]于之训,陈辉堂,王月娟.基于Markov延迟特性的闭环网络控制系统研究[J].控制理论与应用,2002,19(2)：263-267.
[26]张奇智,张彬,张卫东.随机延迟网络控制系统中的分段时戳动态矩阵控制[J].控制与决策,2005,20(8)：873-877.
[27]张小美,郑毓蕃,许建强等.存在时延和数据丢失的网络控制系统的控制器设计[J].信息与控制,2006,35(3)：339-345.
[28]陈虹,史旺旺,刘大年等.基于英特网远程控制的延时预测的改进Smith补偿算法的研究[J].计算机应用研究,2004,21(9)：75-77.
[29]Yu Z Z, Yang M Y. MPC-based Control Methodology in Network Control System[C]. Procceeding of the 5th World Congress Intelligent Control and Automation. California,2002:1361-1365.
[30]Liu G P, Rees D. Stability criteria of networked predictive control systems with random network delay[C].Proceedings of the 44th IEEE Conference on Decision and Control,2005:203-208.
[31]田仲.DMC在网络控制系统中的应用[J].控制工程,2004,11(2)：121-124.
[32]Yu J Y, Mei Y M, Yu S M. MPC-based method dealing with vacant sampling and data rejection in networked control systems[C]. Proceedings of the 3rd Intemauond Conference on Machine Learning and Cyhemetics,2004:574-578.
[33]Mu J X, Liu G P, Rees D. Design of Robust Networked Predictive Control Systems[C]. Proceedings of the American Control Conference,2005:638-643.
[34]Tang P L, Clarence W. Stability and Optimality of Constrained Model Predictive Control with Future Input Buffering in Networked Control Systems[C]. Proceedings of the American Control Conference, 2005:1245-1250.
[35]陈虹,史旺旺.基于英特网远程控制系统的改进广义预测控制方法[J].电机与控制学报,2005,9(6)：565-569.
[36]赵辉,邓燕,王红君,岳有军.基于预测控制的网络时延补偿策略研究[J].仪器仪表学报,2008,29(9)：1923-1928.
[37]邓睿,汤贤铭,俞金寿.动态矩阵控制在网络时延补偿中的应用研究[J].自动化仪表,2010,31(5)：10-12.
[38]Kim W J, Kun J, Ambike A. Networked Real-Time Control Strategies Dealing with Stochastic Time Delays and Packet Losses[C]. Proceedings of the American Control Conference,2005:621-626.
[39]Yang C, Zhu S, Kong W Z et al. Application of generalized predictive control in networked control system[J]. Journal of Zhejiang University, SCIENCE A,2006,7(2):225-233.
[40]Lee S, Lee S H, Lee K C, et al.Intelligent Performance management of networks for advanced manufacturing systems[J]. Transactions on Industrial Electronics,2001,8(4):731-741.
[41]Lian F L. Analysis, design, modeling and control of networked control systems[D]. Michigan: University of Michigan,2001.
[42]Lee K C, Lee S. Remote controller design of networked control system using genetic algorithm[C]. Proceeding of IEEE International Symposium on Industrial Electronics,2001:1845-1850.
[43]Lee S, Lee S H, Lee K C. Remote fuzzy logic control for networked control systems[C].Proceedings of the 27th Annual Conference of the Industrial Electronics Society,2001:1822-1827.
[44]Almutairi N B, Chow M Y. PI parameterization using adaptive fuzzy modulation (AFM) for networked control systems(I):Partial adaptation partial adaptation [C].Proceedings of the 28th IEEE Annual Conference of the Industrial Electronics Society,2002:3152-3157.
[45]Almutairi N B, Chow M Y. PI parameterization using adaptive fuzzy modulation (AFM) for networked control systems(II):Full adaptation [C] Proceedings of the 28th IEEE Annual Conference of the Industrial Electronics Society,2002:3158-3163.
[46]邓玮璍,费敏锐.非线性网络控制系统的T-S模糊H∞控制与数值仿真[J].系统仿真学报,2010,22(7)：1651-1653,1659.
[47]Branicky M S, Phillips SM, Zhang W. Scheduling and feedback co-design for networked control systems[C]. Proceedings of IEEE Conference on Decision and Control,2002(2):1211-1217.
[48]Liu J W S, Lin K J, Shih W K, et al. Algorithms for scheduling imprecise computations[J]. IEEE Transactions on Computers,1991,24(5):58-68.
[49]Sha L, Rajkumar R, Lehoczky J. Priority inheritance protocols:an approcach to real-time synchronization [J]. IEEE Transactions on Computers,1990,39(9):1175-1185.
[50]Baker T. Stack-based scheduling of priority real-time[J]. Real-time Systems,1991,3(1):67-79Z
[51]Liu C L, Laylan J W. Scheduling algorithms for multiprogramming in a hard real-time environment[J]. Journal of the ACM,1973,20(1):46-61.
[52]洪锡军.无线自组网路由协议研究[J].计算机工程,2005,31(8)：105-107.
[53]Hong S H, Kim Y C. Implementation of a bandwidth allocation scheme in a token-passing field-bus network[J]. Instrumentation and Measurement,2002,51(2):246-251.
[54刘鲁源,万仁君,李斌.基于TTCAN协议的网络控制系统静态调度算法的研究[J].控制与决策,2004,19(7)：813-816.
[55]张慧娟,翟鸿鸣,周丽华.实时协同的调度算法研究[J].计算机工程与设计,2004,25(9)：1447-1450.
[56]年梅.通过链路失效预测机制提高AODV协议的性能[J].计算机应用,2005,25(6)：1251-1256.
[57]沈艳,郭兵.网络控制系统便采样周期智能动态调度策略[J].四川大学学报,2010,42(1)：162-164.
[58]谢柏林,方京华,王华.网络化控制系统的信息调度与稳定性研究[J].控制与决策,2004,19(5)：589-591.
[59]Otanez P, Moyne J, Tilbury D.Using dead-bands to reduce communication in networked control system[C]. Proeeedings of the Ameriean Control Conferenee, Anchorage, USA,2002:615-619
[60]刘宁,刘怀,费树岷.网络控制系统中任务与信息的优化调度[J].东南大学学报,2007,37(4)：606-609.
[61]白涛.网络控制系统的性能分析与调度优化[D].上海：上海交通大学,2005.
[62]陈丹丹,夏立.网络控制系统中混合调度算法的研究[J].计算机工程,2008,34(24)：94-96.
[63]Zuberi K M, Shin K G. Design and Implementation of Efficient Message Scheduling for Controller Area Network[J]. IEEE Transaction on Computers,2000,49(2):182-188.
[64]王斌杰,吴卿,赵俊杰.基于汽车电子网络的CAN总线简化型混合调度算法[J].机电工程,2009,26(6)：54-57.
[65]蒋宏江.网络控制系统时延在线测量及其补偿方法研究[D].杭州：浙江大学,2006.
[66]王庆鹏,谈大龙,陈宁.基于Internet的机器人控制中的网络时延测试分析[J].机器人,2001,23(4)：316-231.
[67]王永骥,杨业,吴浩.基于SVM的Internet网络时延分析及预测[J].华中科技大学学报(自然科学版),2006,34(5)：89-90.
[68]司风琪,洪军,许治皋.基于改进Elman网络的动态系统测量数据检验方法[J].东南大学学报,2005,35(1)：50-54.
[69]杨丽曼,李运华.网络控制系统的时延和负载分析[J].控制与决策,2006,21(1)：68-72.
[70]冯晓东.基于工业以太网的网络控制系统及其应用[D].上海：上海交通大学,2003.
[71]杨位钦,顾岚.时间序列分析与动态数据建模[M].北京：北京工业学院出版社,1986.
[72]张海勇,马孝江,盖强.一种新的时变参数AR模型分析方法[J].大连理工大学学报,2002,42(2)：238-241.
[73]杨绿溪.现代数字信号处理[M].北京：科学出版社,2007.
[74]吕振肃,熊景松.一种改进的变步长LMS自适应算法[J].信号处理,2008,24(1)：144-146.
[75]Ray A. Introduction to networking for integrated control systems [J]. IEEE Control Systems Magzine, 1989,9(1):76-79.
[76]Li S B, Wang Z, Sun Y X. Delay-dependent controller design for networked control systems with long time delays:an iterative LMI method[C]. Proceedings of the 5th World Congress on Intelligent Control and Automation, Hangzhou, P.R.China,2004:1338-1342.
[77]Zhang W, Branicky M S, Phillips S M. Stability of networked control systems[J]. IEEE Control Systems Magazine,2001,21(1):84-99.
[78]樊卫华,蔡骅,吴晓蓓等.具有延时和数据包丢失的网络控制系统的稳定性[J].南京理工大学学报,2004,28(5)：465-468.
[79]邱占芝,张庆灵.有时延和数据包丢失的网络控制系统控制器设计[J].控制与决策,2006,21(6)：625-630.
[80]陈虹,严法高,史旺旺等.网络控制系统中考虑动态延时的广义预测控制算法[J].信息与控制,2008,37(02)：224-227
[81]李奇安,褚健.对角CARIMA模型多变量广义预测控制改进算法[J].控制理论与应用,2007(03)：423-426.
[82]王伟.广义预测控制理论及其应用[M].北京：科学出版社,1998.
[83]梁晓明,刘福才,王娟.基于状态空间模型的广义预测控制快速算法[J].计算机仿真,2009,26(4)：335-338.
[84]Mont L A, Antsaklis P J. On the model-based control of networked systems [J]. Automatica,2003, 39(2):1837-1843.
[85]Ma X H,XIE J Y.An observer-based compensator for net-worked control systems [J]. International Journal of Modeling Identification and Control,2007,2(2):169-175.
[86]王艳,纪志成,谢柏林等.基于变采样周期方法的网络控制系统协同设计[J].系统仿真学报,2008,20(8)：2109-2111.
[87]樊金荣.变采样周期网络控制系统的状态反馈设计[J].中南民族大学学报(自然科学版),2010,29(2)：65-67.
[88]沈艳,郭兵.网络控制系统变采样周期智能动态调度策略[J].四川工程大学学报(工程科学版),2010,42(1)：162-166.
[89]Zhang H L, Jing Y W, Zhang S Y. Controller Design for Networked Control Systems with Active Varying Sampling Period [J]. Journal of System Simulation,2009,21(22):72-75.
[90]Marti P, Yepez J, Velasco M, et al. Managing quality-of-control in networked based control systems by controller and message scheduling co-design[J].IEEE Transactions on Industrial Electronics.2004,51 (6):1159-1167.
[91]Huang J, Wu P D, Xiu Z, et al. Variable-sampling process in Internet-based motion control system[J]. Control and Decision,2005,20(7):755-763.
[92]薛艳,刘克,张俊.变采样网络控制系统的建模与分析[J].计算机应用,2007,27(2)：272-274.
[93]黄杰,吴平东,修震等.基于因特网的运动控制系统中变采样过程的研究[J].控制与决策.2005,20(7)：755-758,763.
[94]曹斌,陈龙.基于采样周期可变控制策略[J].自动化学报,1992,18(4)：482-486.
[95]Branicky M S, Phillips S M, Zhang W. Scheduling and feedback co-design for networked control systems [C]. Proceedings of the IEEE Conference on Decision and Control. Piscataway, NJ,USA: IEEE,2002:1211-1217.
[96]He J Q, Zhang H C, Jing Y Z. An integrated control and scheduling optimization method of networked control systems[J].Journal of Electronic Science and Technology of China,2004,2(2):56-59.
[97]Velasco M, Fuertes J M, Lin C X, etal. A control approach to bandwidth management in networked control systems [A]. Pro-ceedings of the Industrial Electronics Conference[C]. Piscataway, NJ, USA: IEEE,2004:2343-2348.
[98]夏峰,孙优贤.多回路网络化控制系统级联反馈调度[J].信息与控制,2007,36(3)：328-333.
[99]高政南,樊卫华,陈庆伟等.基于模糊反馈的网络控制系统分层调度策略[J].南京理工大学学报(自然科学版),2010,34(4)：491-502.
[100]Li Z X, Wang W L, Chen X M. Optimal Bandwidth Scheduling for Resource-constrained Networks[J]. ACTA AUTOMATICA SINICA,2009,35(4):443-448.
[101]Marti P, Yepez J, Velasco M, Villa R, Fuertes J M. Managing quaiity-of-control in networked based control systems by controller and message scheduling co-design[J]. IEEE Transactions on Industrial Electronics.2004,51(6):1159-1167.
[102]Yepez J, Malti P, Fuertes J M. Control loop scheduling paradigm in distributed control systems[C]. Proceedings of the 29th Annual Conference of the IEEE industrial Electronics Society. Roanoke, USA: IEEE,2003:1441-1446.
[103]刘琦,孔峰,张雪林.网络化控制系统的时变采样周期及反馈调度策略[J].计算机工程与应用,2011,47(16)：239-241.
[104]王艳.网络控制系统的控制与调度研究[D].南京：南京理工大学,2006.
[2]Yang T C. Networked control system:a brief survey[C]. Proceedings of IEEE Control Theory and Applications,2006,153(4):403-412.
[3]Park H S, Kim Y H, Kim D S, et al. A scheduling method for network-based control systems[J]. IEEE Transactions on Control Systems Technology,2002,10(3):318-330.
[4]Richard J P. Time-delay systems:an overview of some recent advances and openproblems[J]. Automatica,2003,39(10):1667-1694.
[5]Nilsson J, Bernhardsson B, Wittenmark B. Stochastic analysis and control of real time systems with random time delays [J]. Automatica,1998,34(1):57-64.
[6]Ray A, Halevi Y. Integrated communication and control systems:part Ⅰ-analysis and part Ⅱ-design considerations[J]. Journal of Dynamic Systems,Measurement, and Control.1988,110(4):367-381.
[7]Lian F L, Moyne J, Tilbury D M. Network design consideration for distributed control systems[J]. IEEE Transactions on Control Systems Technology,2002,10(2):297-307.
[8]Ye H. Wireless local area networks in the manufacturing industry[C]. Proceedings of the American Control Conference. Chicago, Illinois,2000:2363-2367.
[9]Nilsson J. Real-time control systems with delays[D]. Sweden:Lund Institute of Technology,1998.
[10]Lawrenz W. CAN system engineering:from theory to practical applications[M]. New York:Springer-Verlag,1997.
[11]马卫国.具有时延和丢包的的鲁棒网络控制系统研究[D].大连：大连理工大学,2008.
[12]Palopoli L, Abeni L, Buttazzo G, et al. Real-time control system analysis:an integrated approach[C]. The 21st IEEE Real-Time Systems Symposium, Orlando, Florida, USA,2000:131-140.
[13]王万良,蒋一波,李祖欣等.网络控制与调度方法及其应用[M].北京：科学技术出版社,2009.
[14]Zhang W. Stability analysis of networked control systems[D]. Cleveland:Case Western Reserve University,2001.
[15]Walsh G C, Ye H. Scheduling of networked control systems[J]. IEEE Control Systems Magazine, 2001,21(1):57-65.
[16]Nillsson J, Bernhardsson B. LQG control over a Markov communication network[C]. Procceeding of the 36th IEEE CDC. San Diego, California,1997:4586-4591.
[17]Lincoln B, Bemhardsson B. Optimal control over networks with long random delays[C]. Proceedings of the international symposium on mathematical theory of networks and systems,2000:84-90.
[18]朱其新,胡寿松,侯霞.长时滞网络控制系统随机稳定性研究[J].东南大学学报(自然科学版),2003,33(3)：368-371.
[19]朱其新,胡寿松.网络控制系统的分析与建模[J].信息与控制,2003,32(1)：5-8,13.
[20]Ma C L, Fang H J. Stochastic stabilization analysis of networked control systems[J]. Journal of SystemsEngineering and Eleetronic,2007,18(1):137-141.
[21]Hu S S, Zhu Q X. Stochastic optimal control and analysis of stability of networked control systems with long delay. Automatica,2003,39(11):1877-1884.
[22]杨业,王永骥,徐建省.输出反馈网络控制系统的随机时滞补偿.华中科技大学学报(自然科学版),2006,34(5)：95-98.
[23]朱其新,胡寿松.网络控制系统的随机输出反馈控制[J].应用科学学报,2004,22(1)：71-75.
[24]白涛,吴智铭,杨根科.网络化控制系统中的抖动优化调度算法[J].控制与决策,2004,19(4)：397-401.
[25]于之训,陈辉堂,王月娟.基于Markov延迟特性的闭环网络控制系统研究[J].控制理论与应用,2002,19(2)：263-267.
[26]张奇智,张彬,张卫东.随机延迟网络控制系统中的分段时戳动态矩阵控制[J].控制与决策,2005,20(8)：873-877.
[27]张小美,郑毓蕃,许建强等.存在时延和数据丢失的网络控制系统的控制器设计[J].信息与控制,2006,35(3)：339-345.
[28]陈虹,史旺旺,刘大年等.基于英特网远程控制的延时预测的改进Smith补偿算法的研究[J].计算机应用研究,2004,21(9)：75-77.
[29]Yu Z Z, Yang M Y. MPC-based Control Methodology in Network Control System[C]. Procceeding of the 5th World Congress Intelligent Control and Automation. California,2002:1361-1365.
[30]Liu G P, Rees D. Stability criteria of networked predictive control systems with random network delay[C].Proceedings of the 44th IEEE Conference on Decision and Control,2005:203-208.
[31]田仲.DMC在网络控制系统中的应用[J].控制工程,2004,11(2)：121-124.
[32]Yu J Y, Mei Y M, Yu S M. MPC-based method dealing with vacant sampling and data rejection in networked control systems[C]. Proceedings of the 3rd Intemauond Conference on Machine Learning and Cyhemetics,2004:574-578.
[33]Mu J X, Liu G P, Rees D. Design of Robust Networked Predictive Control Systems[C]. Proceedings of the American Control Conference,2005:638-643.
[34]Tang P L, Clarence W. Stability and Optimality of Constrained Model Predictive Control with Future Input Buffering in Networked Control Systems[C]. Proceedings of the American Control Conference, 2005:1245-1250.
[35]陈虹,史旺旺.基于英特网远程控制系统的改进广义预测控制方法[J].电机与控制学报,2005,9(6)：565-569.
[36]赵辉,邓燕,王红君,岳有军.基于预测控制的网络时延补偿策略研究[J].仪器仪表学报,2008,29(9)：1923-1928.
[37]邓睿,汤贤铭,俞金寿.动态矩阵控制在网络时延补偿中的应用研究[J].自动化仪表,2010,31(5)：10-12.
[38]Kim W J, Kun J, Ambike A. Networked Real-Time Control Strategies Dealing with Stochastic Time Delays and Packet Losses[C]. Proceedings of the American Control Conference,2005:621-626.
[39]Yang C, Zhu S, Kong W Z et al. Application of generalized predictive control in networked control system[J]. Journal of Zhejiang University, SCIENCE A,2006,7(2):225-233.
[40]Lee S, Lee S H, Lee K C, et al.Intelligent Performance management of networks for advanced manufacturing systems[J]. Transactions on Industrial Electronics,2001,8(4):731-741.
[41]Lian F L. Analysis, design, modeling and control of networked control systems[D]. Michigan: University of Michigan,2001.
[42]Lee K C, Lee S. Remote controller design of networked control system using genetic algorithm[C]. Proceeding of IEEE International Symposium on Industrial Electronics,2001:1845-1850.
[43]Lee S, Lee S H, Lee K C. Remote fuzzy logic control for networked control systems[C].Proceedings of the 27th Annual Conference of the Industrial Electronics Society,2001:1822-1827.
[44]Almutairi N B, Chow M Y. PI parameterization using adaptive fuzzy modulation (AFM) for networked control systems(I):Partial adaptation partial adaptation [C].Proceedings of the 28th IEEE Annual Conference of the Industrial Electronics Society,2002:3152-3157.
[45]Almutairi N B, Chow M Y. PI parameterization using adaptive fuzzy modulation (AFM) for networked control systems(II):Full adaptation [C] Proceedings of the 28th IEEE Annual Conference of the Industrial Electronics Society,2002:3158-3163.
[46]邓玮璍,费敏锐.非线性网络控制系统的T-S模糊H∞控制与数值仿真[J].系统仿真学报,2010,22(7)：1651-1653,1659.
[47]Branicky M S, Phillips SM, Zhang W. Scheduling and feedback co-design for networked control systems[C]. Proceedings of IEEE Conference on Decision and Control,2002(2):1211-1217.
[48]Liu J W S, Lin K J, Shih W K, et al. Algorithms for scheduling imprecise computations[J]. IEEE Transactions on Computers,1991,24(5):58-68.
[49]Sha L, Rajkumar R, Lehoczky J. Priority inheritance protocols:an approcach to real-time synchronization [J]. IEEE Transactions on Computers,1990,39(9):1175-1185.
[50]Baker T. Stack-based scheduling of priority real-time[J]. Real-time Systems,1991,3(1):67-79Z
[51]Liu C L, Laylan J W. Scheduling algorithms for multiprogramming in a hard real-time environment[J]. Journal of the ACM,1973,20(1):46-61.
[52]洪锡军.无线自组网路由协议研究[J].计算机工程,2005,31(8)：105-107.
[53]Hong S H, Kim Y C. Implementation of a bandwidth allocation scheme in a token-passing field-bus network[J]. Instrumentation and Measurement,2002,51(2):246-251.
[54刘鲁源,万仁君,李斌.基于TTCAN协议的网络控制系统静态调度算法的研究[J].控制与决策,2004,19(7)：813-816.
[55]张慧娟,翟鸿鸣,周丽华.实时协同的调度算法研究[J].计算机工程与设计,2004,25(9)：1447-1450.
[56]年梅.通过链路失效预测机制提高AODV协议的性能[J].计算机应用,2005,25(6)：1251-1256.
[57]沈艳,郭兵.网络控制系统便采样周期智能动态调度策略[J].四川大学学报,2010,42(1)：162-164.
[58]谢柏林,方京华,王华.网络化控制系统的信息调度与稳定性研究[J].控制与决策,2004,19(5)：589-591.
[59]Otanez P, Moyne J, Tilbury D.Using dead-bands to reduce communication in networked control system[C]. Proeeedings of the Ameriean Control Conferenee, Anchorage, USA,2002:615-619
[60]刘宁,刘怀,费树岷.网络控制系统中任务与信息的优化调度[J].东南大学学报,2007,37(4)：606-609.
[61]白涛.网络控制系统的性能分析与调度优化[D].上海：上海交通大学,2005.
[62]陈丹丹,夏立.网络控制系统中混合调度算法的研究[J].计算机工程,2008,34(24)：94-96.
[63]Zuberi K M, Shin K G. Design and Implementation of Efficient Message Scheduling for Controller Area Network[J]. IEEE Transaction on Computers,2000,49(2):182-188.
[64]王斌杰,吴卿,赵俊杰.基于汽车电子网络的CAN总线简化型混合调度算法[J].机电工程,2009,26(6)：54-57.
[65]蒋宏江.网络控制系统时延在线测量及其补偿方法研究[D].杭州：浙江大学,2006.
[66]王庆鹏,谈大龙,陈宁.基于Internet的机器人控制中的网络时延测试分析[J].机器人,2001,23(4)：316-231.
[67]王永骥,杨业,吴浩.基于SVM的Internet网络时延分析及预测[J].华中科技大学学报(自然科学版),2006,34(5)：89-90.
[68]司风琪,洪军,许治皋.基于改进Elman网络的动态系统测量数据检验方法[J].东南大学学报,2005,35(1)：50-54.
[69]杨丽曼,李运华.网络控制系统的时延和负载分析[J].控制与决策,2006,21(1)：68-72.
[70]冯晓东.基于工业以太网的网络控制系统及其应用[D].上海：上海交通大学,2003.
[71]杨位钦,顾岚.时间序列分析与动态数据建模[M].北京：北京工业学院出版社,1986.
[72]张海勇,马孝江,盖强.一种新的时变参数AR模型分析方法[J].大连理工大学学报,2002,42(2)：238-241.
[73]杨绿溪.现代数字信号处理[M].北京：科学出版社,2007.
[74]吕振肃,熊景松.一种改进的变步长LMS自适应算法[J].信号处理,2008,24(1)：144-146.
[75]Ray A. Introduction to networking for integrated control systems [J]. IEEE Control Systems Magzine, 1989,9(1):76-79.
[76]Li S B, Wang Z, Sun Y X. Delay-dependent controller design for networked control systems with long time delays:an iterative LMI method[C]. Proceedings of the 5th World Congress on Intelligent Control and Automation, Hangzhou, P.R.China,2004:1338-1342.
[77]Zhang W, Branicky M S, Phillips S M. Stability of networked control systems[J]. IEEE Control Systems Magazine,2001,21(1):84-99.
[78]樊卫华,蔡骅,吴晓蓓等.具有延时和数据包丢失的网络控制系统的稳定性[J].南京理工大学学报,2004,28(5)：465-468.
[79]邱占芝,张庆灵.有时延和数据包丢失的网络控制系统控制器设计[J].控制与决策,2006,21(6)：625-630.
[80]陈虹,严法高,史旺旺等.网络控制系统中考虑动态延时的广义预测控制算法[J].信息与控制,2008,37(02)：224-227
[81]李奇安,褚健.对角CARIMA模型多变量广义预测控制改进算法[J].控制理论与应用,2007(03)：423-426.
[82]王伟.广义预测控制理论及其应用[M].北京：科学出版社,1998.
[83]梁晓明,刘福才,王娟.基于状态空间模型的广义预测控制快速算法[J].计算机仿真,2009,26(4)：335-338.
[84]Mont L A, Antsaklis P J. On the model-based control of networked systems [J]. Automatica,2003, 39(2):1837-1843.
[85]Ma X H,XIE J Y.An observer-based compensator for net-worked control systems [J]. International Journal of Modeling Identification and Control,2007,2(2):169-175.
[86]王艳,纪志成,谢柏林等.基于变采样周期方法的网络控制系统协同设计[J].系统仿真学报,2008,20(8)：2109-2111.
[87]樊金荣.变采样周期网络控制系统的状态反馈设计[J].中南民族大学学报(自然科学版),2010,29(2)：65-67.
[88]沈艳,郭兵.网络控制系统变采样周期智能动态调度策略[J].四川工程大学学报(工程科学版),2010,42(1)：162-166.
[89]Zhang H L, Jing Y W, Zhang S Y. Controller Design for Networked Control Systems with Active Varying Sampling Period [J]. Journal of System Simulation,2009,21(22):72-75.
[90]Marti P, Yepez J, Velasco M, et al. Managing quality-of-control in networked based control systems by controller and message scheduling co-design[J].IEEE Transactions on Industrial Electronics.2004,51 (6):1159-1167.
[91]Huang J, Wu P D, Xiu Z, et al. Variable-sampling process in Internet-based motion control system[J]. Control and Decision,2005,20(7):755-763.
[92]薛艳,刘克,张俊.变采样网络控制系统的建模与分析[J].计算机应用,2007,27(2)：272-274.
[93]黄杰,吴平东,修震等.基于因特网的运动控制系统中变采样过程的研究[J].控制与决策.2005,20(7)：755-758,763.
[94]曹斌,陈龙.基于采样周期可变控制策略[J].自动化学报,1992,18(4)：482-486.
[95]Branicky M S, Phillips S M, Zhang W. Scheduling and feedback co-design for networked control systems [C]. Proceedings of the IEEE Conference on Decision and Control. Piscataway, NJ,USA: IEEE,2002:1211-1217.
[96]He J Q, Zhang H C, Jing Y Z. An integrated control and scheduling optimization method of networked control systems[J].Journal of Electronic Science and Technology of China,2004,2(2):56-59.
[97]Velasco M, Fuertes J M, Lin C X, etal. A control approach to bandwidth management in networked control systems [A]. Pro-ceedings of the Industrial Electronics Conference[C]. Piscataway, NJ, USA: IEEE,2004:2343-2348.
[98]夏峰,孙优贤.多回路网络化控制系统级联反馈调度[J].信息与控制,2007,36(3)：328-333.
[99]高政南,樊卫华,陈庆伟等.基于模糊反馈的网络控制系统分层调度策略[J].南京理工大学学报(自然科学版),2010,34(4)：491-502.
[100]Li Z X, Wang W L, Chen X M. Optimal Bandwidth Scheduling for Resource-constrained Networks[J]. ACTA AUTOMATICA SINICA,2009,35(4):443-448.
[101]Marti P, Yepez J, Velasco M, Villa R, Fuertes J M. Managing quaiity-of-control in networked based control systems by controller and message scheduling co-design[J]. IEEE Transactions on Industrial Electronics.2004,51(6):1159-1167.
[102]Yepez J, Malti P, Fuertes J M. Control loop scheduling paradigm in distributed control systems[C]. Proceedings of the 29th Annual Conference of the IEEE industrial Electronics Society. Roanoke, USA: IEEE,2003:1441-1446.
[103]刘琦,孔峰,张雪林.网络化控制系统的时变采样周期及反馈调度策略[J].计算机工程与应用,2011,47(16)：239-241.
[104]王艳.网络控制系统的控制与调度研究[D].南京：南京理工大学,2006.