城市分布式泵站排水系统综合节能与协调优化控制研究
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摘要
城市排水系统属多输入、多目标的广地域分布复杂非线性耦合系统,不合理的排放控制方式易造成泵站高能耗及污水溢出污染。针对城市分布式泵站排水系统综合节能与协调优化控制问题,本论文主要研究内容和成果如下：
(1)建立了基于机泵群控制、具有时滞和相互链级关系的分布式泵站排水控制系统模型。依据机泵相似律推导出调速特性模型通式,以及基于指数律的机泵调速特性数值模型。探讨了一种基于机泵调速特性模型的实时流量优化测算方法,通过实验检验了该方法的有效性。
(2)以分布式泵站的节能运行为目标,分析了降低静扬程和动扬程的综合节能机理,并给出了适用于不同工况的两种机泵调速节能优化方法：1)针对扬程变化幅度大且不易控制、或扬程与机泵效率比值不满足递减规律的工况,推导了机泵保持等效运行的充要条件,从而得到一种跟随静扬程变化的自适应高效控制法；2)对于静扬程易自主调节且扬程效率比可满足递减规律的一类工况,综合考虑机泵功率与效率,可得依据扬程效率比的节能法。通过实验比较了两种节能控制法的节能效果。
(3)针对广地域城市排水系统的协调优化需求,以及引入网络控制后带来的控制品质下降问题,构造了城市排水系统的分层协调控制结构。推导求证了区域泵站控制系统可控和可观测的充要条件。给出了一种初值匹配参数自适应辨识方法,以及结合该方法的多模型预测函数控制(PFC)法；仿真结果表明,将该方法用于区域泵站的闭环控制,系统辨识效果优于采用ARMAX模型的参数辨识方法,且具有较好的控制鲁棒性。
(4)为改善广地域分布系统工况差异性带来的合流制溢流/分流制溢流(CSO/SSO)问题,提出了一种适用于分布式泵站排水系统的流量协调优化调度方法。引入相互作用预测法,结合流量协调优化调度法,将最优控制转化为最优控制和协调优化调度的多目标综合协调优化。仿真结果表明,当入流量不超过各级泵站的排水能力之和时,综合协调优化能根据工况差异有效利用各分布泵站排水能力,确保全局无溢流,不受时滞和决策变量变化的影响。
(5)设计了一个基于开放标准以太网和Internet的多回路并行C/S网络结构,实现了城市分布式泵站排水网络控制系统中多类型、多回路控制器的网络协调优化调度,为基于分层控制结构的分布式泵站排水系统综合协调优化控制提供了软件平台。
Urban drainage systems are non-linear coupled system with multi-input and multi-objective complexity of the wide geographical distribution. Unreasonable emission control method will cause high energy consumption of pumps and pollution of sewage overflow. Aiming at the problem of comprehensive energy saving and coordinative optimization control of distributed pumping stations in urban drainage systems, the main research topics and contributions of the dissertation are:
(1) A pump group control based urban drainage control systems model was established to describe the urban drainage systems containing unexpected pipeline delay and mutual relations between pumping stations. According to the affinity laws of pump, a general formula for variable-speed characteristic of pump group was derived, then an exponential law based numerical model of variable-speed pump group was obtained. Based on the proposed numerical model, an optimal real-time flow measurement method was discussed. The effectiveness of the measurement method was tested through experiments.
(2) Take the energy-saving operation of distributed pumping stations as the target, the energy-saving mechanism that integrates reducing static head and dynamic head was analyzed. Then, two optimize energy-saving methods for variable-speed pump which are applicable to different conditions were presented: 1) A high efficient self-adaptive control method follows the variation of static head. This method is suitable for the situation that large range of static head is difficult to control and the ratio of head and efficiency is not satisfied with the law of diminishing.2) An integrated optimal control method considering the power and efficiency of pump simultaneously takes the ratio of head and efficiency as the performance indicator. This method is suitable for the situation that static head is easy to self-regulation and the ratio of head and efficiency is satisfied with the law of diminishing. The energy-saving effect of two method was compared through experimentation.
(3) Addressing the optimize coordination demand of large geographically distributed urban drainage systems, and the decline in the quality control after the introduction of networked control, A hierarchical coordinate urban drainage networked control systems was presented. An adaptive parameter estimation law with initial value matching was proposed. Based on the proposed law, a multi-model switching control method integrated of predictive functional control (PFC) was developed. The simulation results show that it has better performance of system identification that applying the proposed parameter estimation law to Regional Station closed-loop control systems instead of using ARMAX model, and the proposed control method has good robustness.
(4) In order to improve Combined Sewer Overflow / Sanitary Sewer Overflow (CSO / SSO) problem brought about by differences in operating conditions of spatially distributed drainage systems, a coordinated discharge scheduling method was discussed,which is adapt to distributed pumping stations in urban drainage systems. By the discharge scheduling method and introduction of the interaction prediction method, optimal control will be converted into multi-objective optimization integrating optimal control and comprehensive scheduling. The simulation results show that coordinative optimization is able to effective use of the capacity of the distributed drainage pumping stations in terms of conditions diversity when the inflow does not exceed the total capacity of drainage pumping station in every level, which ensures overall none sewer overflow. This coordinative optimization method does not affected by the changes of pipeline delay and decision-making variables.
(5) A multi-channel, parallel network architecture based on the open standards Ethernet and Internet was designed. In the basis of the architecture, coordinative network scheduling of multi-type and multi-loop controllers of distributed pumping stations in urban drainage networked control systems was implemented, which provide a software platform for optimal hierarchical control of the coordination of distributed pumping stations in urban drainage systems.
(1)建立了基于机泵群控制、具有时滞和相互链级关系的分布式泵站排水控制系统模型。依据机泵相似律推导出调速特性模型通式,以及基于指数律的机泵调速特性数值模型。探讨了一种基于机泵调速特性模型的实时流量优化测算方法,通过实验检验了该方法的有效性。
(2)以分布式泵站的节能运行为目标,分析了降低静扬程和动扬程的综合节能机理,并给出了适用于不同工况的两种机泵调速节能优化方法：1)针对扬程变化幅度大且不易控制、或扬程与机泵效率比值不满足递减规律的工况,推导了机泵保持等效运行的充要条件,从而得到一种跟随静扬程变化的自适应高效控制法；2)对于静扬程易自主调节且扬程效率比可满足递减规律的一类工况,综合考虑机泵功率与效率,可得依据扬程效率比的节能法。通过实验比较了两种节能控制法的节能效果。
(3)针对广地域城市排水系统的协调优化需求,以及引入网络控制后带来的控制品质下降问题,构造了城市排水系统的分层协调控制结构。推导求证了区域泵站控制系统可控和可观测的充要条件。给出了一种初值匹配参数自适应辨识方法,以及结合该方法的多模型预测函数控制(PFC)法；仿真结果表明,将该方法用于区域泵站的闭环控制,系统辨识效果优于采用ARMAX模型的参数辨识方法,且具有较好的控制鲁棒性。
(4)为改善广地域分布系统工况差异性带来的合流制溢流/分流制溢流(CSO/SSO)问题,提出了一种适用于分布式泵站排水系统的流量协调优化调度方法。引入相互作用预测法,结合流量协调优化调度法,将最优控制转化为最优控制和协调优化调度的多目标综合协调优化。仿真结果表明,当入流量不超过各级泵站的排水能力之和时,综合协调优化能根据工况差异有效利用各分布泵站排水能力,确保全局无溢流,不受时滞和决策变量变化的影响。
(5)设计了一个基于开放标准以太网和Internet的多回路并行C/S网络结构,实现了城市分布式泵站排水网络控制系统中多类型、多回路控制器的网络协调优化调度,为基于分层控制结构的分布式泵站排水系统综合协调优化控制提供了软件平台。
Urban drainage systems are non-linear coupled system with multi-input and multi-objective complexity of the wide geographical distribution. Unreasonable emission control method will cause high energy consumption of pumps and pollution of sewage overflow. Aiming at the problem of comprehensive energy saving and coordinative optimization control of distributed pumping stations in urban drainage systems, the main research topics and contributions of the dissertation are:
(1) A pump group control based urban drainage control systems model was established to describe the urban drainage systems containing unexpected pipeline delay and mutual relations between pumping stations. According to the affinity laws of pump, a general formula for variable-speed characteristic of pump group was derived, then an exponential law based numerical model of variable-speed pump group was obtained. Based on the proposed numerical model, an optimal real-time flow measurement method was discussed. The effectiveness of the measurement method was tested through experiments.
(2) Take the energy-saving operation of distributed pumping stations as the target, the energy-saving mechanism that integrates reducing static head and dynamic head was analyzed. Then, two optimize energy-saving methods for variable-speed pump which are applicable to different conditions were presented: 1) A high efficient self-adaptive control method follows the variation of static head. This method is suitable for the situation that large range of static head is difficult to control and the ratio of head and efficiency is not satisfied with the law of diminishing.2) An integrated optimal control method considering the power and efficiency of pump simultaneously takes the ratio of head and efficiency as the performance indicator. This method is suitable for the situation that static head is easy to self-regulation and the ratio of head and efficiency is satisfied with the law of diminishing. The energy-saving effect of two method was compared through experimentation.
(3) Addressing the optimize coordination demand of large geographically distributed urban drainage systems, and the decline in the quality control after the introduction of networked control, A hierarchical coordinate urban drainage networked control systems was presented. An adaptive parameter estimation law with initial value matching was proposed. Based on the proposed law, a multi-model switching control method integrated of predictive functional control (PFC) was developed. The simulation results show that it has better performance of system identification that applying the proposed parameter estimation law to Regional Station closed-loop control systems instead of using ARMAX model, and the proposed control method has good robustness.
(4) In order to improve Combined Sewer Overflow / Sanitary Sewer Overflow (CSO / SSO) problem brought about by differences in operating conditions of spatially distributed drainage systems, a coordinated discharge scheduling method was discussed,which is adapt to distributed pumping stations in urban drainage systems. By the discharge scheduling method and introduction of the interaction prediction method, optimal control will be converted into multi-objective optimization integrating optimal control and comprehensive scheduling. The simulation results show that coordinative optimization is able to effective use of the capacity of the distributed drainage pumping stations in terms of conditions diversity when the inflow does not exceed the total capacity of drainage pumping station in every level, which ensures overall none sewer overflow. This coordinative optimization method does not affected by the changes of pipeline delay and decision-making variables.
(5) A multi-channel, parallel network architecture based on the open standards Ethernet and Internet was designed. In the basis of the architecture, coordinative network scheduling of multi-type and multi-loop controllers of distributed pumping stations in urban drainage networked control systems was implemented, which provide a software platform for optimal hierarchical control of the coordination of distributed pumping stations in urban drainage systems.
引文
[1]Siljak, D. D.& Stipanovic, D. M. Organically-structured control[C]. Proceedings of the American Control Conference. Piscat-away, NJ, USA:IEEE,2001:2736-2742.
[2]Tan, C., Dabke, K. P.& Mein,R.G.. Modeling and control of sewer flow for reduced cost operation of a sewage pumping station[J].IEEE Transaction on Systems, Man and Cybernatics,1988,18(5):807-813.
[3]Diebbar, Y. & Kadota, P. T. Estimating sanitary flows using neural networks[J]. Water Science And Technology,1998,38(10):215-222.
[4]Mohammad Jamshidi. Large-scale systems:modeling, control, and fuzzy logic[M]. Prentice-Hall PTR, Englewood Cliffs, NJ,1997:183-189.
[5]Siljak, D. D. Large-scale dynamic systems:stability and structure[M]. New York, USA:North-Holland,1978.
[6]Park, H.Y. and Johnson, T. J. Hydrodynamic modeling in solving combined sewer problems:a case study[J]. Water Resource,1998,32(6):1948-1956.
[7]Hsu, M. H.& Chen, S. H. Inundation simulation for urban drainage basin with storm sewer system [J]. Journal of Hydrology,2000(234):21-37.
[8]Previdi, F., Lovera, M.& Mambretti, S. Identification of urban drainage network rainfall-runoff black-box models[C]. Proceedings of the 1998 IEEE International Conference on Control Applications Trieste, Italy 1-4 September,1998(2):1255-1259.
[9]Schmitt,T.G., Thomas,M.,& Ettrich, N. Analysis and modeling of flooding in urban drainage systems[J]. Journal of Hydrology,2004,299(3-4):300-311.
[10]Pappenberger, F., Beven, K. & Horritt, M., et al. Uncertainty in the calibration of effective roughness parameters in HEC-RAS using inundation and downstream level observations[J]. Journal of Hydrology, 2005(302):46-69.
[11]Pappenberger, E, Frodsham, K.& Beven, K. J., et al. Fuzzy set approach to calibrating distributed flood inundation models using remote sensing observations[J]. Hydrology & Earth System Sciences,2006,10:1-14.
[12]Thomdahl, S.& Willems, P. Probabilistic modelling of overflow, surcharge, and flooding in urban drainage using the firstorder reliability method and parameterization of local rain series[J]. Water Research,2008,42(1):455-466.
[13]Thorndahl, S., Beven, K. J., Jensen, J. B., et al. Event based uncertainty assessment in urban drainage modelling, applying the GLUE methodology[J]. Journal of Hydrology,2008(357):421-437.
[14]Andrea C., Francesca P.& Rodolfo S. S. Water reservoir control under economic, social and environmental constraints[J]. Automatica,2008(44):1595-1607.
[15]Ulanicki, B., Kahler, J.& Coulbeck, B. Modeling the efficiency and power characteristics of a pump group[J]. Journal of Water Resources Planning and Management,2008,134(1):84-93.
[16]吴时强.城市暴雨雨水水质管理模型简介[J].水利水运科学研究,1996,12(4)：364-369.
[17]汪雄海,张龙.污水泵站模糊自学习控制系统[J].电工技术学报,2002,17(5)100,101-104.
[18]汪雄海,石宏宇.污水泵站系统的预测控制[J].电工技术学报,2003,18(5)：79-82,86.
[19]石宏宇,周旭强,汪雄海.基于遗传算法的污水泵站机组控制[J].电气自动化,2003，25(3)：26-27,47.
[20]Yagi, S., Shiba, S. Application of genetic algorithms and fuzzy control to a combined sewer station[J]. Water Science And Technology,1999,39(9):217-224.
[21]Ermolin, Y. A. Mathematical modelling for optimized control of Moscow's sewer network[J]. Applied Mathematical Modelling, July,1999,23(7):543-556.
[22]Ermolin, Y. A. Ordinary operating conditions of large channels of Moscow's sewerage network[J]. Irrig. Drain.Engrg. ASCE,1996,122(3):145-148.
[23]Ermolin, Y. A. Estimation of raw sewage discharge resulting from sewer network failing[J]. Urban Water,2001(3):271-276.
[24]Rowe, R.& Kathula, V. Application of new sewer condition assessment methodology measures the relative conveyance performance and risks impacts of FOG and other pipe defects[C]. Collection Systems Conf. Proc. Water Environment Federation 2004.
[25]Guan, X., Luh, P. B. & Yan, H. An optimization-based method for unit commitment[J]. Electrical Power & Energy Systems,1992,14(1):9-17.
[26]Kazarlis, S. A., Bakirtzis, A. G. & Petridis, V. A genetic algorithm solution to the unit commitment problem[J]. IEEE Transactions on Power Systems,1996, 11(1):83-92.
[27]Maifeld, T. T. & Sheble, G. B. Genetic-based unit commitment. IEEE Transactions on Power Systems, 1996,11(3):1359-1370.
[28]Maeda, M., Mizushima, H. & Ito, K. Development of the real-time control (RTC) system for Tokyo sewage system[J]. Water Science and Technology,2005,51(2):213-220
[29]Shirley C., Robert P., Steve B., et al. Annotated Bibliography of Urban Wet Weather Flow Literature from 1996 through 2005[R]. September 2007.
[30]US EPA. Combined Sewer Overflow (CSO) control policy[S],FederalRegister,Tuesday,April 19, 1994,59(75).
[31]US EPA.RePort to Congress, Implementation and Enforcement of the Combined Sewer Overflow Control policy[R],EPA833-R-01-003,2001.
[32]US EPA.Innovative urban wet-weather flow management system[R]. Washington, DC, US EPA water planning division,1999
[33]Bachand, M. L., Gilbert, M. B. Innovative Solution:A combined tunnel option for wastewater applications[C]. PIPELINES 2005:Optimizing Pipeline Design, Operations, and Maintainance in Today's Economy Proc. Pipeline Division Specialty Conf. Am. Society of Civil Engineers,2005: 289-301.
[34]Szabo, J. G., Buchberger,.S. G. & Bishop, P. L. Performance of wet weather treatment facility for control of combined sewer overflows:Case study in Cincinnati, Ohio[J]. Journal of Environment Engineering,2005,131(3):375-386.
[35]Lee, R. K. Sizing replacement interceptors:Beyond ten states standards[C]. Proc. Pipeline Division Specialty Conf., PIPELINES:Optimizing Pipeline Design, Operations, and Maintenance in Today's Economy. Am. Society of Civil Engineers.2005,601-614.
[36]Lee, R. K. Interpreting storm flow data to determine types of infiltration and inflow[C]. Proc. Pipeline Division Specialty Conf., PIPELINES:Optimizing Pipeline Design, Operations, and Maintenance in Today's Economy.Am. Society of Civil Engineers.2005,497-509.
[37]Faure, D., Payrastre, O. & Auchet, P. Radar-based alert system to operate a sewerage network: Relevance and operational effectiveness after several years of use[J]. Water Science Technologl. 2005,51(2):203-211.
[38]Mitchell, P. S., Stevens, P. L. Getting more from flow monitoring how to maximize the value of sewer flow monitoring information[C]. Proc. Pipeline Division Specialty Conf., PIPELINES 2005: Optimizing Pipeline Design, Operations, and Maintenance in Today's Economy. Am. Society of Civil Engineers.2005,615-630.
[39]Zhang, Z. Flow data, inflow/infiltration ratio, and autoregressive error models[J]. Journal of Environment Engineering.2005,131(3):343-349.
[40]Luyckx, G, Vaes, G.& Berlamont, J. Solids separation efficiency of combined sewer overflows[J]. Water Science Technologl.2005,51(2):71-78.
[41]Buyer, M., Vazquez, J. & Bremond, B.Model isation du comportement hydraulique des deversoirs d'orage lateraux en regime transcritique (Numerical modelling of the hydraulic behaviour of lateral storm weirs in a transcritical regime)[J]. (In French). Revue des Sciences de I'Eau.2005,18(1):25-46.
[42]Martin, P., Pelletier, G. & Colas, H., et al. Global predictive real-time control of Quebec Urban Community's Westerly Sewer Network[J]. Water Science and Technology 2001,43 (7),123-130.
[43]Martin, P., Hubert C.& Pierre L., et al. Global optimal real-time control of the Quebec urban drainage system[J]. Environmental Modelling & Software,2005,20:401-413.
[44]Figueras, J., Cembrano, G.& Puig, V., et al.CORAL off-line:an object-oriented tool for optimal control of sewer networks[C].Computer Aided Control System Design,2002 IEEE International Symposium,Glasgow,Scotland,U.K.18-20 Sept.2002:224-229.
[45]Cembrano, G., Quevedo, J.& Salamero, M., et al. Optimal control of urban drainage systems. A case study[J]. Control Engineering Practice. January,2004,12(1),1-9.
[46]Huang, D.& Sing, K.N. State feedback control of uncertain networked control systems with random time delays[J]. IEEE Transactions on Automatic Control,2008,53(3),829-834
[47]诸静.智能预测控制及其应用[M].杭州：浙江大学出版社,2002：174-177.
[48]Kim, Y. H., Park, H. S.& Kwon, W. H.Stability and a scheduling method for network-based control systems[J].IEEE IECON 96.1996:934-939.
[49]Walsh, G.C., Ye, H.& Bushnell, L. G. Stability analysis of networked control systems [C]. Proceedings of the 1999 American Control Conference. Piscataway, NJ, USA:IEEE,1999.2876-2880.
[50]Kim, W. J., Kun J.& Ambike A. Real-time operating environment for networked control systems[J].IEEE Transactions on Automation Science and Engineering,2006,3(3),287-296.
[51]Hjalmarsson, H.& Gevers, M. Special section on algorithms and applications of iterative feedback tuning[J]. Control Engineering Practice.,2003,11:1021-1021
[52]Trumpy, S.& Gagnaire, M. Evolution of Internet technologies[C], Proceeding IEEE,2004,92:1355-1359.
[53]Olfati, S.R.& Murray, R.M.Consensus problems in networks of agents with switching topology and time-delays[J]. IEEE Transactions on Automatic Control,2004,49:1520-1533.
[54]Chen, J., Gu, K.,& Kharitonov, V. Stability of time-delay systems[M]. Birkhauser, Boston, Massachusetts,2002.
[55]Manutch, M. Z. Time-delay systems:analysis, optimization and applications [M]. North-A.Holland,1987
[56]Yang, T.C. Computational delay in digital and adaptive controllers[C].IEE Control Conference, Brighton, UK,1990.
[57]Yang, T.C., Zhang, J.H.,& Yu, H. A new decentralised controller design method with application to power-system stabiliser design[J]. Control Engineering Practice,1999,7:537-545.
[58]Ukai, H., Nakamura, K.& Matsui, N. DSP- and GPS-based synchronized measurement system of harmonics in wide-area distribution system[J]. IEEE Transactions on Industrial Electronics,2003, 50:1159-1164.
[59]Heinert, B. GPS-based time synchronization improves plant reliability [J]. Power Engineering,2003, 107:38-43.
[60]Bhowmik, S., Tomsovic, K.,& Bose, A. Communication models for third party load frequency control[J]. IEEE Transactions on Power Systems,2004,19:543-548.
[61]Tipsuwan, Y., Chow, M. Y. Control methodologies in networked control systems [J]. Control Engineering Practice,2003,11 (10):1099-1111.
[62]Yang, T.C. Networked control system-a brief survey[J], IEE Proceedings Control Theory & Applications,2006,153(4):403-412.
[63]Lee, K. C.,& Lee, S. Performance evaluation of switched Ethernet for real-time industrial communications [J]. Computer Standards & Interfaces,2002,24:411-423.
[64]Field, T., Harder, U.,& Harrison, P. Network traffic behaviour in switched Ethernet systems [J]. Performance Evaluation,2004,58:243-260.
[65]Zhang, W., Branicky, M.S.,& Phillips, S.M. Stability of networked control systems [J].IEEE Control System Magazine,2001,21:84-99.
[66]Hartman, M., Lowiec, E.& Boguslawski, P. Water pumping stations remote control system in depression areas based GSM-900 cellular communications system [C]. Modern Problems of Radio Engineering, Telecommunications and Computer Science, Proceedings of the International Conference. Tcset'2002,Ukraine,18-23 Feb.2002:291-293.
[67]Farmer, B., Glueckstein, L.& Atanossov, K., et al. Design and integration of supervisory control and data acquisition (SCADA) system, Milwaukee Metropolitan Sewer District. Collection Systems 2004 Conf.Proc. Water Environment Federation.2004.
[68]Yang, S.H., Chen, X.& Alty, J. L. Design issues and implementation of internet-based process control Systems [J]. Control Engineering Practice,2003,11:709-720.
[69]Yang, L.L.& Yang, S. H. Multirate control in internet-based control systems [J].IEEE Transactions on Systems, Man, and Cybernetics—Part C:Applications and Reviews,2007,37(2):185-192.
[70]Lingireddy, S.& Woo, D. J. Improved operation of water distribution systems using variable-speed pumps[J]. Journal of Energy Engineering,1998,124(3),90-103.
[71]汪雄海,张龙.污水泵站系统的最优控制策略[J].浙江大学学报(工学版).2002,36(6)：718-721.
[72]伍悦滨,朱蒙生.工程流体力学泵与风机[M].化学工业出版社,2006：243-246.
[73]Coulbeck, B., Orr, C. H.,& Cunningham, A. E. GINAS 5 reference manual. Research Rep. No.56, Water Software Systems, De Montfort Univ., Leicester, U.K.1991
[74]Rossman, L. A. EPANET 2 users manual, U.S.Environmental Protection Agency, Cincinnati,2000.
[75]Walski, T. M., Barnard, T. E.& Harold, E., et al. Waste water collection system modeling and design, Haestad Press, Waterbury, Conn.2004
[76]Ghoneim,A.A. Design optimization of photovoltaic powered water pumping systems[J],Energy Conversion and Management,2006,47(11-12):1449-1463.
[77]詹姆希迪(Jamshidi, Mohammad).大系统建模与控制[M].北京：科学出版社,1986：170-174,197,380-381.
[78]Carlos, O. M., Ari I., Vicen(?) P., et al. Objective prioritization using lexicographic minimizers for MPC ofsewer networks[J].IEEE Transactions on Control Systems Technology,2008,16(1):113-120.
[79]Melchers, R.E. Structural reliability—analysis and prediction[M].Ellis Horwood Limited, Chichester, UK,1999..
[80]张承慧,夏东伟,石庆升.计及变频器和电机损耗的全调速泵站效率优化控制[J].电工技术学报,2006,21(5)：52-57.
[81]Mahdi, M. J., Miguel, A.M.& Abbas A. Optimal design and operation of irrigation pumping stations[J]. Journal of Irrigation and Drainage Engineering,2003,129(3):149-154.
[82]Kulkarni, S. R. et al. Model and controller selection policies based on output prediction errors[J]. IEEE Transactions on Automatic Control,1996,41(11):1594-1604.
[83]Thompson, H. A. Wireless and Internet communications technologies for monitoring and control[J]. Control Engineering Practice,12(6),2004:.781-791.
[84]Hespanha, J.P. et al. A Survey of Recent Results in Networked Control Systems[J]. Proceedings of the IEEE,2007,95(1):138-162.
[85]Ogren, P., Fiorelli,E. & Leonard, N. E. Cooperative control of mobile sensor networks:Adaptive gradient climbing in a distributed environment[J], IEEE Transactions on Automatic Control,2004, 49(8):1292-1302.
[86]Seiler, P. and Sengupta, R. Analysis of communication losses in vehicle control problems[C], in Proc. American Control Conference, June.2001,2:1491-1496.
[87]Zhang, W., Branicky, M. S.,& Phillips, S. M. Stability of networked control systems[J]. IEEE Control Systems Magazine, February,2001:84-99.
[88]Huang, B.,& Shah, S. L. Performance assessment of control loops:Theory and applications[M]. New York, NY:Springer.1999
[89]Luo, R. C., Tzou, J. H.& Chang, Y. C. Desktop rapid prototyping system with supervisory control and monitoring through internet[J].IEEE/ASME Trans. Mechatron.,2001,6(4):399-409.
[90]Garcia, C. E., Carelli, R.& Postigo, J. F., et al. Supervisory, control of a telerobotic system: a hybrid control approach[J]. Control Eng. Practice,2003,11(7):805-817.
[91]Walsh, G. C., Hong Y.,& Linda G.Bushnell. Stability analysis of networked control systems[J]. IEEE Transactions on Control Systems Technology,2002,10(3):438-446.
[92]Zhao, Y. B., Liu, G. P.& Rees, D. Integrated predictive control and scheduling co-design for networked control[J].IET Control Theory & Applications,2008,2(1):7-15.
[93]Chai,S.C., Liu,G.P.& Rees,D., et al. Design and practical implementation of Internet-based predictive control of a servo System[J].IEEE Transactions on Control Systems Technology,2008,16(1):158-168.
[94]Qiu, B. & Gooi, H. B. Web-based SCADA Display Systems (WSDS) for access via Internet[J]. IEEE Transactions on Power Systems,2000,15(2):681-686..
[95]Srivastava, A. & Kim, W. J. Internet-based supervisory control with stochastic delay models[C]. in Proc. American Control Conference,, Denver, CO, Jun.2003,1:627-632.
[96]Callaghan, M.J. et al. Client-server architecture for collaborative remote experimentation[J]. Journal of Network and Computer Applications.2007,30:1295-1308.
[97]Al-Kasassbeh M., Adda M. Analysis of mobile agents in network fault management[J]. Journal of Network and Computer Applications,2008,31(4):699-711.
[98]ScadaOnWeb. (2002).
[99]Yang, S. H., Chen, X.& Tan, L., et al. Time delay and data loss compensation for Internet-based process control systems[J]. Transactions of the Institute of Measurement and Control,2005,27(2):103-118.
[100]Elia, N. & Mitter, S. K. Stabilization of linear systems with limited information[J],IEEE Transactions on. Automatic Control,2001,46(9):1384-1400.
[101]Hespanha, J. P., Ortega, A.& Vasudevan, L. Towards the control of linear systems with minimum bit-rate[C], Proc. Int. Symp. Mathematical Theory of Networks and System, Aug.2002.
[102]Braslavsky, J. H., Middleton, R. H.& Freudenberg, J. S. Feedback stabilization over signal-to-noise ratio constrained Channels[C], Proc. American Control Conference, Jun.2004:4903-4908.
[103]Yang, S.H. Remote maintenance of control system performance over the Internet[J]. Control Engineering Practice (2007),15:533-544.
[104]Nilsson, J., Bernhardsson, B.& Wittenmark, B. Stochastic analysis and control of realtime systems with random time delays [J].Automatica,1998,34 (1):57-64.
[105]Nilsson, J. Realtime Control Systems with Delays [D]. Sweden: Lund Institute of Technology,1998.
[106]Zhang, L. Q., Shi, Y. & Chen, T. W., et al. A new method for stabilization of networked control systems with random delays [J]. IEEE Transactions on Automatic Control,2005,50 (8):1177-1181.
[107]Chen, C. H., Lin, C.L.& Hwang, T. S. Stability of networked control systems with time-varying delays[J]. IEEE Communications Letters,2007,11 (3):270-272
[108]Vatanski, N., Georges, J. P.& Aubrun, C., et al. Networked control with delay measurement and estimation[J].Control Engineering Practice,2009,17(2):231-244.
[109]于之训,蒋平,陈辉堂等.具有传输延迟的网络控制系统中状态观测器的设计[J].信息与控制,2000,29(2)：125-130.
[110]Zhang, W. A.& Yu, Li. Output feedback stabilization of networked control systems with packet dropouts[J]. IEEE Transactions on Automatic Control,2007,52(9):1705-1710.
[111]Zhang, W., Branicky, M. S.& Phillips, S. M. Stability of networked control systems[J]. IEEE Control Systems Magazine,2001,21(1):84-99.
[112]Naghshtabrizi, P.& Hespanha, J. Designing observer-based controller for network control system[C]. in Proc.44th Conf. Decision and Contr., Jun.2005(4):2876-2880.
[113]Yue, D., Han, Q. L.& Peng, C. State feedback controller design for networked control systems[J]. IEEE Transactions on Circuits Systems,2004,51(11):640-644.
[114]Sinopoli, B. L., Schenato, M.,& Franceschetti, K., et al. Kalman filtering with intermittent observations[J].IEEE Transactions on Automatic Control,2004,49(9):1453-1464.
[115]Tatikonda, S. Control under communication constrains[D]. Ph.D. dissertation, MIT, Cambridge, MA, 2000.
[116]Smith, S. C. and Seiler, P. Estimation with lossy measurements:Jump estimators for jump systems[J]. IEEE Transactions on Automatic Control,2003,48(12):2163-2171.
[117]Yu, M., Wang, L.& Xie, G., et al. Stabilization of networked control systems with data packet droupout via switched system approach[C]. in IEEE Int. Symp. Computer Aided Control Systems Design, Taipei, Taiwan, Sep.2004:362-367.
[118]Seiler, P.& Sengupta, R. Analysis of communication losses in vehicle control problems[C].in Proc. American Control Conference,Jun.2001,2:1491-1496.
[119]Seiler, P.& Raja, S. An Hinf approach to networked control[J].IEEE Transactions on Automatic Control,2005,50(3):356-364,.
[120]De Farias, D. P., Geromel, J. C.& Do Val, J. B. R. et al. Output feedback control of Markov jump linear systems in continuous time[J].IEEE Transactions on Automatic Control,2000,45(5):944-949.
[121]Lin, H.& Antsaklis, P. J. Stability and persistent disturbance attenuation properties for a class of networked control systems:Switched system approach[J].International Journal of Control 2005,78(18):1447-1458.
[122]Zhang, W. Stability analysis of networked control systems[D]. Ph.D. dissertation, Case Western Reserve Univ., Cleveland, OH,2001.
[123]Yu, M., Wang, L.& Chu, T. Sampled-data stabilization of networked control systems with nonlinearity[J]. IEE Proceedings of Control Theory and Applications.2005,152(6):609-614.
[124]Ling, Q.& Lemmon,M. D. Robust performance of soft real-time networked control systems with data dropouts[C]. In Proc.41st IEEE Conf. Decision Contr., Las Vegas, NV, Dec.2002:1225-1230.
[125]Xiong, J. L.& Lam, J. Stabilization of linear systems over networkswith bounded packet loss[J].Automatica,2007,43(1):80-87.
[126]Zhai, G. S., Hu, B.& Yasuda, K., et al. Qualitative analysis of discrete-time switched systems[C]. in Proc. American Control Conference, Anchorage,AK, May 2002:1880-1885.
[127]Narendra, K. S. Adaptive control using multiple models[J]. IEEE Transactions on Automatic Control, 1997,42(2):171-187.
[128]Narendra, K.S.& Cheng, X. Adaptive control of discrete-time systems using multiple models[J]. IEEE Transactions on Automatic Control,2000,45(9):1669-1686.
[129]席裕庚,王凡.非线性系统预测控制的多模型方法[J].自动化学报,1996,22(4)：456-461,503.
[130]李晓理,王书宁.离散时间系统多模型自适应控制的改进算法[J].电机与控制学报,2002,6(2)：135-139.
[2]Tan, C., Dabke, K. P.& Mein,R.G.. Modeling and control of sewer flow for reduced cost operation of a sewage pumping station[J].IEEE Transaction on Systems, Man and Cybernatics,1988,18(5):807-813.
[3]Diebbar, Y. & Kadota, P. T. Estimating sanitary flows using neural networks[J]. Water Science And Technology,1998,38(10):215-222.
[4]Mohammad Jamshidi. Large-scale systems:modeling, control, and fuzzy logic[M]. Prentice-Hall PTR, Englewood Cliffs, NJ,1997:183-189.
[5]Siljak, D. D. Large-scale dynamic systems:stability and structure[M]. New York, USA:North-Holland,1978.
[6]Park, H.Y. and Johnson, T. J. Hydrodynamic modeling in solving combined sewer problems:a case study[J]. Water Resource,1998,32(6):1948-1956.
[7]Hsu, M. H.& Chen, S. H. Inundation simulation for urban drainage basin with storm sewer system [J]. Journal of Hydrology,2000(234):21-37.
[8]Previdi, F., Lovera, M.& Mambretti, S. Identification of urban drainage network rainfall-runoff black-box models[C]. Proceedings of the 1998 IEEE International Conference on Control Applications Trieste, Italy 1-4 September,1998(2):1255-1259.
[9]Schmitt,T.G., Thomas,M.,& Ettrich, N. Analysis and modeling of flooding in urban drainage systems[J]. Journal of Hydrology,2004,299(3-4):300-311.
[10]Pappenberger, F., Beven, K. & Horritt, M., et al. Uncertainty in the calibration of effective roughness parameters in HEC-RAS using inundation and downstream level observations[J]. Journal of Hydrology, 2005(302):46-69.
[11]Pappenberger, E, Frodsham, K.& Beven, K. J., et al. Fuzzy set approach to calibrating distributed flood inundation models using remote sensing observations[J]. Hydrology & Earth System Sciences,2006,10:1-14.
[12]Thomdahl, S.& Willems, P. Probabilistic modelling of overflow, surcharge, and flooding in urban drainage using the firstorder reliability method and parameterization of local rain series[J]. Water Research,2008,42(1):455-466.
[13]Thorndahl, S., Beven, K. J., Jensen, J. B., et al. Event based uncertainty assessment in urban drainage modelling, applying the GLUE methodology[J]. Journal of Hydrology,2008(357):421-437.
[14]Andrea C., Francesca P.& Rodolfo S. S. Water reservoir control under economic, social and environmental constraints[J]. Automatica,2008(44):1595-1607.
[15]Ulanicki, B., Kahler, J.& Coulbeck, B. Modeling the efficiency and power characteristics of a pump group[J]. Journal of Water Resources Planning and Management,2008,134(1):84-93.
[16]吴时强.城市暴雨雨水水质管理模型简介[J].水利水运科学研究,1996,12(4)：364-369.
[17]汪雄海,张龙.污水泵站模糊自学习控制系统[J].电工技术学报,2002,17(5)100,101-104.
[18]汪雄海,石宏宇.污水泵站系统的预测控制[J].电工技术学报,2003,18(5)：79-82,86.
[19]石宏宇,周旭强,汪雄海.基于遗传算法的污水泵站机组控制[J].电气自动化,2003，25(3)：26-27,47.
[20]Yagi, S., Shiba, S. Application of genetic algorithms and fuzzy control to a combined sewer station[J]. Water Science And Technology,1999,39(9):217-224.
[21]Ermolin, Y. A. Mathematical modelling for optimized control of Moscow's sewer network[J]. Applied Mathematical Modelling, July,1999,23(7):543-556.
[22]Ermolin, Y. A. Ordinary operating conditions of large channels of Moscow's sewerage network[J]. Irrig. Drain.Engrg. ASCE,1996,122(3):145-148.
[23]Ermolin, Y. A. Estimation of raw sewage discharge resulting from sewer network failing[J]. Urban Water,2001(3):271-276.
[24]Rowe, R.& Kathula, V. Application of new sewer condition assessment methodology measures the relative conveyance performance and risks impacts of FOG and other pipe defects[C]. Collection Systems Conf. Proc. Water Environment Federation 2004.
[25]Guan, X., Luh, P. B. & Yan, H. An optimization-based method for unit commitment[J]. Electrical Power & Energy Systems,1992,14(1):9-17.
[26]Kazarlis, S. A., Bakirtzis, A. G. & Petridis, V. A genetic algorithm solution to the unit commitment problem[J]. IEEE Transactions on Power Systems,1996, 11(1):83-92.
[27]Maifeld, T. T. & Sheble, G. B. Genetic-based unit commitment. IEEE Transactions on Power Systems, 1996,11(3):1359-1370.
[28]Maeda, M., Mizushima, H. & Ito, K. Development of the real-time control (RTC) system for Tokyo sewage system[J]. Water Science and Technology,2005,51(2):213-220
[29]Shirley C., Robert P., Steve B., et al. Annotated Bibliography of Urban Wet Weather Flow Literature from 1996 through 2005[R]. September 2007.
[30]US EPA. Combined Sewer Overflow (CSO) control policy[S],FederalRegister,Tuesday,April 19, 1994,59(75).
[31]US EPA.RePort to Congress, Implementation and Enforcement of the Combined Sewer Overflow Control policy[R],EPA833-R-01-003,2001.
[32]US EPA.Innovative urban wet-weather flow management system[R]. Washington, DC, US EPA water planning division,1999
[33]Bachand, M. L., Gilbert, M. B. Innovative Solution:A combined tunnel option for wastewater applications[C]. PIPELINES 2005:Optimizing Pipeline Design, Operations, and Maintainance in Today's Economy Proc. Pipeline Division Specialty Conf. Am. Society of Civil Engineers,2005: 289-301.
[34]Szabo, J. G., Buchberger,.S. G. & Bishop, P. L. Performance of wet weather treatment facility for control of combined sewer overflows:Case study in Cincinnati, Ohio[J]. Journal of Environment Engineering,2005,131(3):375-386.
[35]Lee, R. K. Sizing replacement interceptors:Beyond ten states standards[C]. Proc. Pipeline Division Specialty Conf., PIPELINES:Optimizing Pipeline Design, Operations, and Maintenance in Today's Economy. Am. Society of Civil Engineers.2005,601-614.
[36]Lee, R. K. Interpreting storm flow data to determine types of infiltration and inflow[C]. Proc. Pipeline Division Specialty Conf., PIPELINES:Optimizing Pipeline Design, Operations, and Maintenance in Today's Economy.Am. Society of Civil Engineers.2005,497-509.
[37]Faure, D., Payrastre, O. & Auchet, P. Radar-based alert system to operate a sewerage network: Relevance and operational effectiveness after several years of use[J]. Water Science Technologl. 2005,51(2):203-211.
[38]Mitchell, P. S., Stevens, P. L. Getting more from flow monitoring how to maximize the value of sewer flow monitoring information[C]. Proc. Pipeline Division Specialty Conf., PIPELINES 2005: Optimizing Pipeline Design, Operations, and Maintenance in Today's Economy. Am. Society of Civil Engineers.2005,615-630.
[39]Zhang, Z. Flow data, inflow/infiltration ratio, and autoregressive error models[J]. Journal of Environment Engineering.2005,131(3):343-349.
[40]Luyckx, G, Vaes, G.& Berlamont, J. Solids separation efficiency of combined sewer overflows[J]. Water Science Technologl.2005,51(2):71-78.
[41]Buyer, M., Vazquez, J. & Bremond, B.Model isation du comportement hydraulique des deversoirs d'orage lateraux en regime transcritique (Numerical modelling of the hydraulic behaviour of lateral storm weirs in a transcritical regime)[J]. (In French). Revue des Sciences de I'Eau.2005,18(1):25-46.
[42]Martin, P., Pelletier, G. & Colas, H., et al. Global predictive real-time control of Quebec Urban Community's Westerly Sewer Network[J]. Water Science and Technology 2001,43 (7),123-130.
[43]Martin, P., Hubert C.& Pierre L., et al. Global optimal real-time control of the Quebec urban drainage system[J]. Environmental Modelling & Software,2005,20:401-413.
[44]Figueras, J., Cembrano, G.& Puig, V., et al.CORAL off-line:an object-oriented tool for optimal control of sewer networks[C].Computer Aided Control System Design,2002 IEEE International Symposium,Glasgow,Scotland,U.K.18-20 Sept.2002:224-229.
[45]Cembrano, G., Quevedo, J.& Salamero, M., et al. Optimal control of urban drainage systems. A case study[J]. Control Engineering Practice. January,2004,12(1),1-9.
[46]Huang, D.& Sing, K.N. State feedback control of uncertain networked control systems with random time delays[J]. IEEE Transactions on Automatic Control,2008,53(3),829-834
[47]诸静.智能预测控制及其应用[M].杭州：浙江大学出版社,2002：174-177.
[48]Kim, Y. H., Park, H. S.& Kwon, W. H.Stability and a scheduling method for network-based control systems[J].IEEE IECON 96.1996:934-939.
[49]Walsh, G.C., Ye, H.& Bushnell, L. G. Stability analysis of networked control systems [C]. Proceedings of the 1999 American Control Conference. Piscataway, NJ, USA:IEEE,1999.2876-2880.
[50]Kim, W. J., Kun J.& Ambike A. Real-time operating environment for networked control systems[J].IEEE Transactions on Automation Science and Engineering,2006,3(3),287-296.
[51]Hjalmarsson, H.& Gevers, M. Special section on algorithms and applications of iterative feedback tuning[J]. Control Engineering Practice.,2003,11:1021-1021
[52]Trumpy, S.& Gagnaire, M. Evolution of Internet technologies[C], Proceeding IEEE,2004,92:1355-1359.
[53]Olfati, S.R.& Murray, R.M.Consensus problems in networks of agents with switching topology and time-delays[J]. IEEE Transactions on Automatic Control,2004,49:1520-1533.
[54]Chen, J., Gu, K.,& Kharitonov, V. Stability of time-delay systems[M]. Birkhauser, Boston, Massachusetts,2002.
[55]Manutch, M. Z. Time-delay systems:analysis, optimization and applications [M]. North-A.Holland,1987
[56]Yang, T.C. Computational delay in digital and adaptive controllers[C].IEE Control Conference, Brighton, UK,1990.
[57]Yang, T.C., Zhang, J.H.,& Yu, H. A new decentralised controller design method with application to power-system stabiliser design[J]. Control Engineering Practice,1999,7:537-545.
[58]Ukai, H., Nakamura, K.& Matsui, N. DSP- and GPS-based synchronized measurement system of harmonics in wide-area distribution system[J]. IEEE Transactions on Industrial Electronics,2003, 50:1159-1164.
[59]Heinert, B. GPS-based time synchronization improves plant reliability [J]. Power Engineering,2003, 107:38-43.
[60]Bhowmik, S., Tomsovic, K.,& Bose, A. Communication models for third party load frequency control[J]. IEEE Transactions on Power Systems,2004,19:543-548.
[61]Tipsuwan, Y., Chow, M. Y. Control methodologies in networked control systems [J]. Control Engineering Practice,2003,11 (10):1099-1111.
[62]Yang, T.C. Networked control system-a brief survey[J], IEE Proceedings Control Theory & Applications,2006,153(4):403-412.
[63]Lee, K. C.,& Lee, S. Performance evaluation of switched Ethernet for real-time industrial communications [J]. Computer Standards & Interfaces,2002,24:411-423.
[64]Field, T., Harder, U.,& Harrison, P. Network traffic behaviour in switched Ethernet systems [J]. Performance Evaluation,2004,58:243-260.
[65]Zhang, W., Branicky, M.S.,& Phillips, S.M. Stability of networked control systems [J].IEEE Control System Magazine,2001,21:84-99.
[66]Hartman, M., Lowiec, E.& Boguslawski, P. Water pumping stations remote control system in depression areas based GSM-900 cellular communications system [C]. Modern Problems of Radio Engineering, Telecommunications and Computer Science, Proceedings of the International Conference. Tcset'2002,Ukraine,18-23 Feb.2002:291-293.
[67]Farmer, B., Glueckstein, L.& Atanossov, K., et al. Design and integration of supervisory control and data acquisition (SCADA) system, Milwaukee Metropolitan Sewer District. Collection Systems 2004 Conf.Proc. Water Environment Federation.2004.
[68]Yang, S.H., Chen, X.& Alty, J. L. Design issues and implementation of internet-based process control Systems [J]. Control Engineering Practice,2003,11:709-720.
[69]Yang, L.L.& Yang, S. H. Multirate control in internet-based control systems [J].IEEE Transactions on Systems, Man, and Cybernetics—Part C:Applications and Reviews,2007,37(2):185-192.
[70]Lingireddy, S.& Woo, D. J. Improved operation of water distribution systems using variable-speed pumps[J]. Journal of Energy Engineering,1998,124(3),90-103.
[71]汪雄海,张龙.污水泵站系统的最优控制策略[J].浙江大学学报(工学版).2002,36(6)：718-721.
[72]伍悦滨,朱蒙生.工程流体力学泵与风机[M].化学工业出版社,2006：243-246.
[73]Coulbeck, B., Orr, C. H.,& Cunningham, A. E. GINAS 5 reference manual. Research Rep. No.56, Water Software Systems, De Montfort Univ., Leicester, U.K.1991
[74]Rossman, L. A. EPANET 2 users manual, U.S.Environmental Protection Agency, Cincinnati,2000.
[75]Walski, T. M., Barnard, T. E.& Harold, E., et al. Waste water collection system modeling and design, Haestad Press, Waterbury, Conn.2004
[76]Ghoneim,A.A. Design optimization of photovoltaic powered water pumping systems[J],Energy Conversion and Management,2006,47(11-12):1449-1463.
[77]詹姆希迪(Jamshidi, Mohammad).大系统建模与控制[M].北京：科学出版社,1986：170-174,197,380-381.
[78]Carlos, O. M., Ari I., Vicen(?) P., et al. Objective prioritization using lexicographic minimizers for MPC ofsewer networks[J].IEEE Transactions on Control Systems Technology,2008,16(1):113-120.
[79]Melchers, R.E. Structural reliability—analysis and prediction[M].Ellis Horwood Limited, Chichester, UK,1999..
[80]张承慧,夏东伟,石庆升.计及变频器和电机损耗的全调速泵站效率优化控制[J].电工技术学报,2006,21(5)：52-57.
[81]Mahdi, M. J., Miguel, A.M.& Abbas A. Optimal design and operation of irrigation pumping stations[J]. Journal of Irrigation and Drainage Engineering,2003,129(3):149-154.
[82]Kulkarni, S. R. et al. Model and controller selection policies based on output prediction errors[J]. IEEE Transactions on Automatic Control,1996,41(11):1594-1604.
[83]Thompson, H. A. Wireless and Internet communications technologies for monitoring and control[J]. Control Engineering Practice,12(6),2004:.781-791.
[84]Hespanha, J.P. et al. A Survey of Recent Results in Networked Control Systems[J]. Proceedings of the IEEE,2007,95(1):138-162.
[85]Ogren, P., Fiorelli,E. & Leonard, N. E. Cooperative control of mobile sensor networks:Adaptive gradient climbing in a distributed environment[J], IEEE Transactions on Automatic Control,2004, 49(8):1292-1302.
[86]Seiler, P. and Sengupta, R. Analysis of communication losses in vehicle control problems[C], in Proc. American Control Conference, June.2001,2:1491-1496.
[87]Zhang, W., Branicky, M. S.,& Phillips, S. M. Stability of networked control systems[J]. IEEE Control Systems Magazine, February,2001:84-99.
[88]Huang, B.,& Shah, S. L. Performance assessment of control loops:Theory and applications[M]. New York, NY:Springer.1999
[89]Luo, R. C., Tzou, J. H.& Chang, Y. C. Desktop rapid prototyping system with supervisory control and monitoring through internet[J].IEEE/ASME Trans. Mechatron.,2001,6(4):399-409.
[90]Garcia, C. E., Carelli, R.& Postigo, J. F., et al. Supervisory, control of a telerobotic system: a hybrid control approach[J]. Control Eng. Practice,2003,11(7):805-817.
[91]Walsh, G. C., Hong Y.,& Linda G.Bushnell. Stability analysis of networked control systems[J]. IEEE Transactions on Control Systems Technology,2002,10(3):438-446.
[92]Zhao, Y. B., Liu, G. P.& Rees, D. Integrated predictive control and scheduling co-design for networked control[J].IET Control Theory & Applications,2008,2(1):7-15.
[93]Chai,S.C., Liu,G.P.& Rees,D., et al. Design and practical implementation of Internet-based predictive control of a servo System[J].IEEE Transactions on Control Systems Technology,2008,16(1):158-168.
[94]Qiu, B. & Gooi, H. B. Web-based SCADA Display Systems (WSDS) for access via Internet[J]. IEEE Transactions on Power Systems,2000,15(2):681-686..
[95]Srivastava, A. & Kim, W. J. Internet-based supervisory control with stochastic delay models[C]. in Proc. American Control Conference,, Denver, CO, Jun.2003,1:627-632.
[96]Callaghan, M.J. et al. Client-server architecture for collaborative remote experimentation[J]. Journal of Network and Computer Applications.2007,30:1295-1308.
[97]Al-Kasassbeh M., Adda M. Analysis of mobile agents in network fault management[J]. Journal of Network and Computer Applications,2008,31(4):699-711.
[98]ScadaOnWeb. (2002).
[99]Yang, S. H., Chen, X.& Tan, L., et al. Time delay and data loss compensation for Internet-based process control systems[J]. Transactions of the Institute of Measurement and Control,2005,27(2):103-118.
[100]Elia, N. & Mitter, S. K. Stabilization of linear systems with limited information[J],IEEE Transactions on. Automatic Control,2001,46(9):1384-1400.
[101]Hespanha, J. P., Ortega, A.& Vasudevan, L. Towards the control of linear systems with minimum bit-rate[C], Proc. Int. Symp. Mathematical Theory of Networks and System, Aug.2002.
[102]Braslavsky, J. H., Middleton, R. H.& Freudenberg, J. S. Feedback stabilization over signal-to-noise ratio constrained Channels[C], Proc. American Control Conference, Jun.2004:4903-4908.
[103]Yang, S.H. Remote maintenance of control system performance over the Internet[J]. Control Engineering Practice (2007),15:533-544.
[104]Nilsson, J., Bernhardsson, B.& Wittenmark, B. Stochastic analysis and control of realtime systems with random time delays [J].Automatica,1998,34 (1):57-64.
[105]Nilsson, J. Realtime Control Systems with Delays [D]. Sweden: Lund Institute of Technology,1998.
[106]Zhang, L. Q., Shi, Y. & Chen, T. W., et al. A new method for stabilization of networked control systems with random delays [J]. IEEE Transactions on Automatic Control,2005,50 (8):1177-1181.
[107]Chen, C. H., Lin, C.L.& Hwang, T. S. Stability of networked control systems with time-varying delays[J]. IEEE Communications Letters,2007,11 (3):270-272
[108]Vatanski, N., Georges, J. P.& Aubrun, C., et al. Networked control with delay measurement and estimation[J].Control Engineering Practice,2009,17(2):231-244.
[109]于之训,蒋平,陈辉堂等.具有传输延迟的网络控制系统中状态观测器的设计[J].信息与控制,2000,29(2)：125-130.
[110]Zhang, W. A.& Yu, Li. Output feedback stabilization of networked control systems with packet dropouts[J]. IEEE Transactions on Automatic Control,2007,52(9):1705-1710.
[111]Zhang, W., Branicky, M. S.& Phillips, S. M. Stability of networked control systems[J]. IEEE Control Systems Magazine,2001,21(1):84-99.
[112]Naghshtabrizi, P.& Hespanha, J. Designing observer-based controller for network control system[C]. in Proc.44th Conf. Decision and Contr., Jun.2005(4):2876-2880.
[113]Yue, D., Han, Q. L.& Peng, C. State feedback controller design for networked control systems[J]. IEEE Transactions on Circuits Systems,2004,51(11):640-644.
[114]Sinopoli, B. L., Schenato, M.,& Franceschetti, K., et al. Kalman filtering with intermittent observations[J].IEEE Transactions on Automatic Control,2004,49(9):1453-1464.
[115]Tatikonda, S. Control under communication constrains[D]. Ph.D. dissertation, MIT, Cambridge, MA, 2000.
[116]Smith, S. C. and Seiler, P. Estimation with lossy measurements:Jump estimators for jump systems[J]. IEEE Transactions on Automatic Control,2003,48(12):2163-2171.
[117]Yu, M., Wang, L.& Xie, G., et al. Stabilization of networked control systems with data packet droupout via switched system approach[C]. in IEEE Int. Symp. Computer Aided Control Systems Design, Taipei, Taiwan, Sep.2004:362-367.
[118]Seiler, P.& Sengupta, R. Analysis of communication losses in vehicle control problems[C].in Proc. American Control Conference,Jun.2001,2:1491-1496.
[119]Seiler, P.& Raja, S. An Hinf approach to networked control[J].IEEE Transactions on Automatic Control,2005,50(3):356-364,.
[120]De Farias, D. P., Geromel, J. C.& Do Val, J. B. R. et al. Output feedback control of Markov jump linear systems in continuous time[J].IEEE Transactions on Automatic Control,2000,45(5):944-949.
[121]Lin, H.& Antsaklis, P. J. Stability and persistent disturbance attenuation properties for a class of networked control systems:Switched system approach[J].International Journal of Control 2005,78(18):1447-1458.
[122]Zhang, W. Stability analysis of networked control systems[D]. Ph.D. dissertation, Case Western Reserve Univ., Cleveland, OH,2001.
[123]Yu, M., Wang, L.& Chu, T. Sampled-data stabilization of networked control systems with nonlinearity[J]. IEE Proceedings of Control Theory and Applications.2005,152(6):609-614.
[124]Ling, Q.& Lemmon,M. D. Robust performance of soft real-time networked control systems with data dropouts[C]. In Proc.41st IEEE Conf. Decision Contr., Las Vegas, NV, Dec.2002:1225-1230.
[125]Xiong, J. L.& Lam, J. Stabilization of linear systems over networkswith bounded packet loss[J].Automatica,2007,43(1):80-87.
[126]Zhai, G. S., Hu, B.& Yasuda, K., et al. Qualitative analysis of discrete-time switched systems[C]. in Proc. American Control Conference, Anchorage,AK, May 2002:1880-1885.
[127]Narendra, K. S. Adaptive control using multiple models[J]. IEEE Transactions on Automatic Control, 1997,42(2):171-187.
[128]Narendra, K.S.& Cheng, X. Adaptive control of discrete-time systems using multiple models[J]. IEEE Transactions on Automatic Control,2000,45(9):1669-1686.
[129]席裕庚,王凡.非线性系统预测控制的多模型方法[J].自动化学报,1996,22(4)：456-461,503.
[130]李晓理,王书宁.离散时间系统多模型自适应控制的改进算法[J].电机与控制学报,2002,6(2)：135-139.