面向轧制过程的RP-Agent分布式协同控制系统研究
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摘要
随着市场对板材产品的质量、规格与性价比的要求日益提高和市场竞争的日益激烈，加上近年来出现的一些新技术、新工艺的应用，如中厚板全液压矫直机、全液压滚切剪以及双边剪、碳基不锈钢复合材等，使得多液压缸伺服协同控制和过程智能决策控制在现代轧制过程中起着越来越重要的作用，这些也为轧制过程自动化控制系统的研究和进步提出了更高的要求。解决生产过程中出现的新情况和适应这些新工艺的发展，急需一套能够整合信息的过程控制系统，将现场检测传感器、基础自动化、传动自动化和过程自动化等共同组成一个统一的信息高度融合的平台。基于中厚板全液压矫直机的多自由度的四个伺服缸的协同控制，全液压滚切剪两个伺服缸的协同控制，以及作为单台成套设备如何融入全线的过程自动化和工厂的管理自动化等大量工程实践的基础上，论文的研究内容和研究结果如下：
（1）总结了轧制过程计算机控制系统的发展，对轧制过程自动化计算机控制系统的三种架构，以及国内提出的两种架构做了详细的综述。强调了数字化、微型化、网络化、低成本、强计算将是未来的发展方向。
（2）运用Agent的理论与方法，论证了Agent运动协调一致性。提出面向轧制过程的RP-Agent分布式协同控制架构，定义了适合轧制过程的RP-Agent模型，提出该模型由通讯层、协调层和控制层共同构成；定义了RP-Agent模型的核心层即协调层由本体模型、协作模型、计算模型和自学习共同组成。指出协调层是RP-Agent系统对外部环境变化或自身活动所做出的各种反应。以热连轧精轧出口温度控制(FDTC)为例介绍了单个及多个RP-Agent控制群的概念，提出将大问题分解成若干个小问题由两个RP-Agent共同分担求解复杂问题的控制架构方案。通讯、协调和控制都是作为计算机控制系统中的进程资源，当系统中存在两个或两个以上RP-Agent时，提出其中一个RP-Agent为Host RP-Agent作为核心控制器负责整个系统的性能和逻辑以及任务的激活和再分配的策略，其它RP-Agent则定义为Slave RP-Agent，且只做为Host RP-Agent计算能力延伸的策略，从而保证了整个控制系统的协调和有序控制。
（3）采用Gaia开发方法，对RP-Agent进行了详细的需求分析，归纳总结出轧制过程自动化控制系统主要解决的5类问题，在此基础上分别创立了5种系统角色：CommC Role (通讯中心角色), CoorC Role (协调中心角色), ContC Role (控制中心角色),EnviOb Role (环境对象角色), BlackBoard Role (公共黑板角色)。通过对各个角色之间的信息交互关系进行详细的分析，运用Gaia的图形化语言方法建立了系统的交互模型。在角色模型和完善后的交互模型的基础上设计出面向轧制过程的RP-Agent主体模型、服务模型和熟人模型。最后总结了基于Gaia方法的面向RP-Agent的建模全过程。
（4）对轧制过程中的“事件”做了针对性分类。建立了RP-Agent事件驱动的体系结构，定义由Host RP-Agent根据总体负荷决定系统中计算模型的任务分配。建立了环境事件和自身事件由侦听、捕获到分配和处理的全过程，即RP-Agent事件驱动的行为模型。根据本体论的静态知识表示方法描述了RP-Agent控制系统中的所有控制对象的组成及其相互联系，以中厚板全液压滚切剪主操作台的部分对象为实例介绍了如何构建系统的本体知识库。详细分析和介绍了基于事件驱动的RP-Agent内部行为的决策过程和算法的执行过程。通过修改RP-Agent的匹配因子权重的方法提高系统按照设计好的计划执行的能力，使得该算法的可控性和可靠性都得到了增强。
（5）通过OntologyList和RelatedProperties表的实例表明Oracle在轧制过程自动化的控制系统中存在巨大的优势和众多的优点。其次通过对“公共黑板”角色的实现过程，得出“公共黑板”这个角色的建立是解决并行处理、独立设计与调试、求解大而不确定的复杂问题的重要而有效的手段。
（6）介绍了多路液压伺服在轧制过程中的详细应用，提出基于RP-Agent控制系统的结构，通过对动态指令值曲线和动态跟踪策略的试验，验证了基于RP-Agent架构的智能性、协同性和有效性。
With the increasing demands of the plate product quality, specifications andcost-effective and the increasingly fierce market competition, and the newtechnologies and processes such as medium and heavy plate hydraulicstraightening machine, full-hydraulic rolling shear and bilateral scissors,stainless steel composite carbon-base, have been widely applied in recent years.At the same time, the means of achieving modern rolling process actions havegradually evolved into multi-cylinder cooperative control or process intelligentdecision-making control. All the above technologies put forward higherrequirements of the rolling process automation control research anddevelopment. In order to solve the new situations of production process andadapt to these new technology developments, a process control system is eagerlyneeded to integrate information, so that field detection sensor, basic automation,drive automation and process automation can be combined into ahighly-integrated information platform. On the basis of cooperative control offour servo cylinder with multi-degree of freedoms on medium and heavy platefull-hydraulic straightening machine, two servo cylinder collaborative control onthe full-hydraulic rolling shear, and how to integrate into the full range ofprocess automation and factory automation equipment as a single largeengineering practice, the dissertation contents and findings are as follows:
(1) The development of rolling process computer control system has beensummarized, and the three architectures of rolling process automation computercontrol system and two domestic architectures have been detailed illustrated.The digitization, miniaturization, network-based, low-cost, strong computationwill be the future directions of development.
(2) Agent theory and methods were used to demonstrate the Agent motioncoherence. This article first proposed the RP-Agent distributed cooperativecontrol architecture for the rolling process, and introduced the definition of theRP-Agent model for rolling process, the communication layer, coordinationlayer and control layer of the model’s constitutions; together the definition of thecore layer of the RP-Agent model form by coordination layer ontology model,the collaborative model, the computational model and self-learning. Thecoordinative layer was pointed out to be the different reactions of RP-Agentsystem to external environment or their own activities. FDTC was made as anexample to introduce the concept of single and multiple RP-Agent controlgroups. The control framework program, during which a big problem wasbroken down into a number of small issues and two RP-Agents were shared forsolving complex problems, were brought forward. Communication, coordinationand control as the process resources of computer control system, when two ormore RP-Agents are existing in the system, a RP-Agent was defined as the corecontroller of Host RP-Agent to be responsible for the performances and logics ofoverall system and the strategies on task activation and redistribution, otherRP-Agents were defined as Slave RP-Agent only for extending the calculatingability of Host RP-Agent so as to ensure the coordination and orderly control ofthe entire control system.
(3) A detailed requirement analysis was made on RP-Agent by Gaiadevelopment method, the five kinds of problems to be solved in rolling processautomation and control system were summarized, and five system roles werefounded on this basis: CommC role, CoorC role, ContC role, EnviOb role,BlackBoard role. Gaia graphical language was used to build asystematically-interactive model by the detailed analysis on the informationinteractive relationships among the various actors. RP-Agent body model,service model and acquaintance model, which were oriented for the rollingprocess, were designed based on the role model and perfect interaction model.Moreover, the whole Gaia-based and RP-Agent-oriented modeling process wassummarized.
(4) The targeted classification of "events" in the rolling process was made.The architecture of RP-Agent event-driven was built, and the task allocationcalculation model based on the overall load determining system was defined byHost RP-Agent. The whole process of the environmental events and self events,i.e., the RP-Agent event-driven model of behaviors, was established fromlistening, capture and distribution to processing. The static knowledgerepresentation of ontology was used to describe the compositions of all thecontrol objects of RP-Agent control system and their interconnections. Partialobjects of the main console of full-hydraulic medium and heavy plate rollingshear were used as samples to introduce on how to build system ontology. Thedecision-making process of RP-Agent-based event-driven internal behaviors andthe implementation of the algorithm were analyzed and described in detail. Thecontrollability and reliability of the proposed algorithm have been enhanced bymodifying the RP-Agent matching index weights for improving the system’sexecution ability according to the designed plan.
(5) Oracle has been proved to have huge advantages and many meritsthrough the applications of OntologyList and RelatedProperties tables in rollingprocess automation control system. Secondly, through the implementationprocess of "blackboard" role, the establishment of the "blackboard" wasconcluded to be an important and effective means to solve parallel processing,independent design and debugging, as well as the solution of the large anduncertain complex issues.
(6) The multiplex hydraulic servo in the rolling process was introduced indetail, and the RP-Agent-based control system structure was put forward. Basedon the command value dynamic hyperbolic and dynamic tracking strategy, theintelligence, collaborative and effectiveness of RP-Agent architecture have beenvalidated.
（1）总结了轧制过程计算机控制系统的发展，对轧制过程自动化计算机控制系统的三种架构，以及国内提出的两种架构做了详细的综述。强调了数字化、微型化、网络化、低成本、强计算将是未来的发展方向。
（2）运用Agent的理论与方法，论证了Agent运动协调一致性。提出面向轧制过程的RP-Agent分布式协同控制架构，定义了适合轧制过程的RP-Agent模型，提出该模型由通讯层、协调层和控制层共同构成；定义了RP-Agent模型的核心层即协调层由本体模型、协作模型、计算模型和自学习共同组成。指出协调层是RP-Agent系统对外部环境变化或自身活动所做出的各种反应。以热连轧精轧出口温度控制(FDTC)为例介绍了单个及多个RP-Agent控制群的概念，提出将大问题分解成若干个小问题由两个RP-Agent共同分担求解复杂问题的控制架构方案。通讯、协调和控制都是作为计算机控制系统中的进程资源，当系统中存在两个或两个以上RP-Agent时，提出其中一个RP-Agent为Host RP-Agent作为核心控制器负责整个系统的性能和逻辑以及任务的激活和再分配的策略，其它RP-Agent则定义为Slave RP-Agent，且只做为Host RP-Agent计算能力延伸的策略，从而保证了整个控制系统的协调和有序控制。
（3）采用Gaia开发方法，对RP-Agent进行了详细的需求分析，归纳总结出轧制过程自动化控制系统主要解决的5类问题，在此基础上分别创立了5种系统角色：CommC Role (通讯中心角色), CoorC Role (协调中心角色), ContC Role (控制中心角色),EnviOb Role (环境对象角色), BlackBoard Role (公共黑板角色)。通过对各个角色之间的信息交互关系进行详细的分析，运用Gaia的图形化语言方法建立了系统的交互模型。在角色模型和完善后的交互模型的基础上设计出面向轧制过程的RP-Agent主体模型、服务模型和熟人模型。最后总结了基于Gaia方法的面向RP-Agent的建模全过程。
（4）对轧制过程中的“事件”做了针对性分类。建立了RP-Agent事件驱动的体系结构，定义由Host RP-Agent根据总体负荷决定系统中计算模型的任务分配。建立了环境事件和自身事件由侦听、捕获到分配和处理的全过程，即RP-Agent事件驱动的行为模型。根据本体论的静态知识表示方法描述了RP-Agent控制系统中的所有控制对象的组成及其相互联系，以中厚板全液压滚切剪主操作台的部分对象为实例介绍了如何构建系统的本体知识库。详细分析和介绍了基于事件驱动的RP-Agent内部行为的决策过程和算法的执行过程。通过修改RP-Agent的匹配因子权重的方法提高系统按照设计好的计划执行的能力，使得该算法的可控性和可靠性都得到了增强。
（5）通过OntologyList和RelatedProperties表的实例表明Oracle在轧制过程自动化的控制系统中存在巨大的优势和众多的优点。其次通过对“公共黑板”角色的实现过程，得出“公共黑板”这个角色的建立是解决并行处理、独立设计与调试、求解大而不确定的复杂问题的重要而有效的手段。
（6）介绍了多路液压伺服在轧制过程中的详细应用，提出基于RP-Agent控制系统的结构，通过对动态指令值曲线和动态跟踪策略的试验，验证了基于RP-Agent架构的智能性、协同性和有效性。
With the increasing demands of the plate product quality, specifications andcost-effective and the increasingly fierce market competition, and the newtechnologies and processes such as medium and heavy plate hydraulicstraightening machine, full-hydraulic rolling shear and bilateral scissors,stainless steel composite carbon-base, have been widely applied in recent years.At the same time, the means of achieving modern rolling process actions havegradually evolved into multi-cylinder cooperative control or process intelligentdecision-making control. All the above technologies put forward higherrequirements of the rolling process automation control research anddevelopment. In order to solve the new situations of production process andadapt to these new technology developments, a process control system is eagerlyneeded to integrate information, so that field detection sensor, basic automation,drive automation and process automation can be combined into ahighly-integrated information platform. On the basis of cooperative control offour servo cylinder with multi-degree of freedoms on medium and heavy platefull-hydraulic straightening machine, two servo cylinder collaborative control onthe full-hydraulic rolling shear, and how to integrate into the full range ofprocess automation and factory automation equipment as a single largeengineering practice, the dissertation contents and findings are as follows:
(1) The development of rolling process computer control system has beensummarized, and the three architectures of rolling process automation computercontrol system and two domestic architectures have been detailed illustrated.The digitization, miniaturization, network-based, low-cost, strong computationwill be the future directions of development.
(2) Agent theory and methods were used to demonstrate the Agent motioncoherence. This article first proposed the RP-Agent distributed cooperativecontrol architecture for the rolling process, and introduced the definition of theRP-Agent model for rolling process, the communication layer, coordinationlayer and control layer of the model’s constitutions; together the definition of thecore layer of the RP-Agent model form by coordination layer ontology model,the collaborative model, the computational model and self-learning. Thecoordinative layer was pointed out to be the different reactions of RP-Agentsystem to external environment or their own activities. FDTC was made as anexample to introduce the concept of single and multiple RP-Agent controlgroups. The control framework program, during which a big problem wasbroken down into a number of small issues and two RP-Agents were shared forsolving complex problems, were brought forward. Communication, coordinationand control as the process resources of computer control system, when two ormore RP-Agents are existing in the system, a RP-Agent was defined as the corecontroller of Host RP-Agent to be responsible for the performances and logics ofoverall system and the strategies on task activation and redistribution, otherRP-Agents were defined as Slave RP-Agent only for extending the calculatingability of Host RP-Agent so as to ensure the coordination and orderly control ofthe entire control system.
(3) A detailed requirement analysis was made on RP-Agent by Gaiadevelopment method, the five kinds of problems to be solved in rolling processautomation and control system were summarized, and five system roles werefounded on this basis: CommC role, CoorC role, ContC role, EnviOb role,BlackBoard role. Gaia graphical language was used to build asystematically-interactive model by the detailed analysis on the informationinteractive relationships among the various actors. RP-Agent body model,service model and acquaintance model, which were oriented for the rollingprocess, were designed based on the role model and perfect interaction model.Moreover, the whole Gaia-based and RP-Agent-oriented modeling process wassummarized.
(4) The targeted classification of "events" in the rolling process was made.The architecture of RP-Agent event-driven was built, and the task allocationcalculation model based on the overall load determining system was defined byHost RP-Agent. The whole process of the environmental events and self events,i.e., the RP-Agent event-driven model of behaviors, was established fromlistening, capture and distribution to processing. The static knowledgerepresentation of ontology was used to describe the compositions of all thecontrol objects of RP-Agent control system and their interconnections. Partialobjects of the main console of full-hydraulic medium and heavy plate rollingshear were used as samples to introduce on how to build system ontology. Thedecision-making process of RP-Agent-based event-driven internal behaviors andthe implementation of the algorithm were analyzed and described in detail. Thecontrollability and reliability of the proposed algorithm have been enhanced bymodifying the RP-Agent matching index weights for improving the system’sexecution ability according to the designed plan.
(5) Oracle has been proved to have huge advantages and many meritsthrough the applications of OntologyList and RelatedProperties tables in rollingprocess automation control system. Secondly, through the implementationprocess of "blackboard" role, the establishment of the "blackboard" wasconcluded to be an important and effective means to solve parallel processing,independent design and debugging, as well as the solution of the large anduncertain complex issues.
(6) The multiplex hydraulic servo in the rolling process was introduced indetail, and the RP-Agent-based control system structure was put forward. Basedon the command value dynamic hyperbolic and dynamic tracking strategy, theintelligence, collaborative and effectiveness of RP-Agent architecture have beenvalidated.
引文
[1]黄庆学.轧钢机械设计[M].北京:冶金工业出版社,2007
[2]黄庆学,马立峰,李进宝等.新型滚切剪非对称曲柄机构原理[J],机械工程学报,2008,44(5):119-123
[3]马立峰,黄庆学等.新型滚切剪空间剪切机构优化数学模型的建立及应用[J],四川大学学报（工程科学版）,2008,40(2):170-174
[4]楚志兵,黄庆学,马立峰等.滚切式双边剪连杆机构的动力学仿真及实验研究[J],四川大学学报(工程科学版),2011,43(1):247-251
[5]李玉贵,马立峰,黄庆学.单轴双偏心非对称负偏置滚切剪研究[J],钢铁,2008,43(2):51-55
[6] LI Hongjie, HUANG Qingxue, JU CHangjiang, et al. Research and application ofmulti-embedded system cooperative control for plate leveler [J]. ICIC Express Letters,2011,2(6):1321-1327
[7] Gui H L, Huang Q X, Chen Y M. Analysis of the contact problems using mixed fastmulti-pole boundary element method [J], ICIC Express Letters,2010,4(3):1281-1285
[8]王效岗,黄庆学,胡鹰.中厚板辊式矫直过程模型算法修正与应用[J],中国机械工程,2012,23(3):335-338
[9]韩贺永,黄庆学,张洪等.液压矫直机液压伺服系统动态特性分析比较[J].吉林大学学报（工学版）,2012,42(2):372-376
[10]孙一康.适用于轧钢过程的计算机控制系统[J].中国工程科学,2000,.2(1):73-76
[11]孙增圻.计算机控制理论与应用（第二版）[M].北京:清华大学出版社,2008
[12]彭天乾.过程计算机控制系统的性能评价[J].冶金自动化,1986,5:2-9
[13]周希德.控制理论与计算机实时控制[J].北方交通大学学报,1988,1:81-88
[14]阳宪惠.现场总线技术及其应用[M].北京:清华大学出版社,1999
[15] J P Thomesse. A review of the fieldbuses, Aeviews in Control [J],1998,22:35-45
[16] T Blevins, W Wojsznis. Fieldbus Support for Process Analysis [J], ISA Transactions,1996,35(2):177-183
[17]胡学林.可编程控制器原理及应用[M].北京:电子工业出版社,2012
[18]孙优贤.我国工业过程自动化高技术产业化重大进展[J].控制工程,2003,10(2):97-105
[19]郑申白,史东日,马劲红.轧制过程自动化技术[M].北京,化学工业出版社,2009
[20]朱亚斌,沈康.宝钢冷轧3级控制系统L3_L2_L1间通讯实现[J].南京理工大学学报,2005,29(10):199-202
[21]黄天煌.从霍尼韦尔DCS的变迁看过程自动化控制系统的发展趋势[J].自动化博览.2008.S1:30-34
[22]刘复华. TDCS:当代微机控制系统的发展方向[J].武汉工业大学学报.1988.NO.2:263-270
[23]张殿华,王国栋,王君等.四机架热连轧机分布式计算机控制系统[J].冶金自动化,1998.2:9-12
[24]孙一康.冷热轧板带轧机的模型与控制[M].北京:冶金工业出版社,2010
[25]刘玠,孙一康.带钢热连轧计算机控制[M].北京:机械工业出版社,1997
[26]王英,张小真, CSCW协同建组协商策略研究[J].计算机应用,2005,25(3):695-699
[27]魏力,陈昊,李凌等. CSCW中可靠有序的群组通信算法[J].电子科技,2009,22(1):55-59
[28]张志勇,杨林,马建峰等.基于可信计算的CSCW系统访问控制[J].华中科技大学学报(自然科学版),2008,36(1):59-62
[29]高胜,吴林.基于CSCW的遥控焊接机器人系统协同工作模型[J].焊接学报,2007,28(3):9-13
[30]胡斌,陈刚,董金祥.一种用于CSCW系统设计的认知模型[J].计算机工程,2004,30(13):133-135
[31]肖波,张东,诸鸿文.计算机支持的协同工作并发控制策略[J].上海交通大学学报,1999,33(1):101-104
[32]宋海刚,陈学广.计算机支持的协同工作发展述评[J].计算机工程与应用,2004,1:7-11
[33]王国意,史元春,徐光佑.计算机支持的协同工作系统的时序逻辑模型[J],软件学报,1998,9(3):169-173
[34]刘立骐,田华,许维胜等. CSCW研究理论及应用[J].信息与控制,1998, Vol.27,No.3:190-193
[35] Walter Reinhard, Jean Svhweizer, Gerd Volksen, et al. CSCW: Concepts andArchitectures [J]. IEEE Computers,1994,27(5):28-36
[36]王晓丽,洪奕光.多智能体系统分布式控制的研究新进展[J].复杂系统与复杂性科学.2010, Vol.7, No.2-3:70-81
[37]刘金琨,尔联洁.多智能体技术应用综述[J].控制与决策,2001,Vol.16, No.2:133-139
[38]毛新军.面向主体的软件开发[M],北京:清华大学出版社.2005
[39]毛新军,常志明,王戟等.面向Agent的软件工程:现状与挑战[J],计算机研究与发展.2006,43(10):1782-1789
[40] Gerhard Weib. Agent orientation in software engineering [J], The KnowledgeEngineering Review,2001,16(4):349-373
[41] Mao Xinjun, Wang Ji, Chen Jiajia. Modeling the organization structure of multi-agentsystem [C], IAT’2005, Compiegne, France,2005
[42] Michael Wooldridge, Paolo Ciancarini. Agent-oriented software engineering: The state ofthe art [G], In: Proc of AOSE’2001, LNAI1957. Berlin: Springer,2001
[43] Ofer Arazy, Carson C Woo. Analysis and design of agent-oriented information systems[J], The Knowledge Engineering Review,2002,17(3):215-260
[44] K H Dam, M Winikoff. Comparing agent-oriented methodologies [C], The5th Int’lBi-Conference Workshop on Agent-Oriented Information System, Melbourne,2003
[45] Qi Yan, Xinjun Mao, Hong Zhu, et al. Modeling multi-agent system with soft genes,roles and agents [G], In: Proc of AOSE’2004, LNCS3382. Springer,2004.231-245
[46] Yoav Shoham. Agent-oriented programming [J], Artificial Intelligence,1993,60(1):51-92
[47] R H Bordini, M Dastani, J Dix, et al. Programming multi-agent systems [C], Proc of2ndInt’l Workshop ProMAS. Berlin: Springer,2004
[48] Stefan Bussmann, Nicholas R Jennings, Michael Wooldridge, Reuse of interactionprotocols for agent-based control applications [C], In: Proc of AOSE’2002, LNCS2585.Berlin: Springer,2002:73-87
[49] J A Giampapa, O H JuarezEspinosa, K P Sycara, Configuration management formulti-agent systems [C], In: Proc of AGENT2001. New York: ACM Press,2001:230-231
[50] H Zhu, L Shan. Caste-centric modelling of multi-agent systems: The CAMLE modellinglanguage and automated tools [G], In: Model-Driven Software Development, Researchand Pract ice in Software Engineering II. Berlin: Springer,2004
[51] H Zhu, A formal specification language for agent-oriented software engineering [C], In:Proc of AAMAS.2003, New York: ACM Press,2003:1174-1175
[52] A Fuxman, M Pistore, J Mylopoulos, et al. Model checking early requirementsspecifications in tropos [C], IEEE Int’1Sympon Requirements Engineering, Toronto,Canada,2001
[53] Jennings N R. On agent-based software engineering [J], Artificial Intelligence,2000,117(2):277-296
[54]蔡自兴,徐光祐.人工智能及其应用[M].北京:清华大学出版社,2004
[55] MAES P. Modeling adaptive autonomous Agent [J]. Artificial Life,1994,1(1/2):135-162
[56] Wooldrige M, Jennings N R. Intelligent Agents: theory and practice [J]. KnowledgeEngineering Review,1995,10(2):112-152
[57] Reynolds C W. Flocks, herds, and schools: a distributed behavioral model [J]. ComputerGraphics,1987,21:25-34
[58] Vicsek T, Cziro k A, Ben-Jacob E, et al. Novel type of phase transition in a system ofself-driven particles [J]. Phys Rev Letts,1995,75(6):1226-1229
[59] Couzin I D, Krause J, Franks N R, et al. Effective leadership and decision making inanimal groups on the move [J]. Nature,2005,433:513-516
[60] Olfati-Saber R. Flocking for multi-agent dynamic systems: algorithms and theory [J].IEEE Trans Automatic Control,2006,51:401-420
[61] Tanner H G, Jadbabaie A, Pappas G J. Flocking in fixed and switching networks [J].IEEE Transactions on Automatic Control,2007,52(5):863-868
[62] Casbeer D W, Kingston D B, Beard R W, et al. Cooperative forest re surveillance using ateam of small unmanned air vehicles [J]. International Journal of Systems Sciences,2006,37:351-360
[63] Gage D W. Command control for many-robot systems [C]. AUVS92, the NineteenthAnnual AUVS Technical Symposium. Huntsville, Alabama, USA,1992:22-24
[64] Ma C Q, Zhang J F. Necessary and sufficient conditions for consensus ability of linearmulti-agent systems [J]. IEEE Trans on Automatic Control,2010,55(10):1263-1268
[65] Lin Z, Francis B, Maggiore M. State agreement for continuous-time coupled nonlinearsystems [J]. SIAM Journal on Control and Optimization,2007,46(1):288-307
[66] Moreau L. Stability of multi-agent systems with time-dependent communication links [J].IEEE Transitions on Automatic Control,2005,50(2):169-182
[67] Lin P, Jia Y M. Average consensus in networks of multi-agents with both switchingtopology and coupling time-delay [J]. Physical A: Statistical Mechanics and itsApplications,2008,387(1):303-313
[68] Xin Z, Guo L. Synchronization of multi-agent systems without connectivity assumptions[J]. Automatic Control,2009,45(12):2744-2753
[69] Chen F, Chen Z Q, Xiang L Y, et al. reaching a consensus via pinning control [J].Automatic Control,2009,45(5):1215-1220
[70] LYNCH N A. Distributed Algorithms [M]. San Francisco, CA: Morgan Kaufmann,1997
[71] Hong Y, GAO L, CHENG D, et al. Lyapuov-based approach to multi-agent systems withswitching jointly connected interconnection [J]. IEEE transactions on automatic control,2007,52(5):943-948
[72] Y C P Jeff, J M Tenenbaum. An intelligent agent framework for enterprise integration [J],IEEE Transon systems, Man and Cybernetics,1991,21(6):1391-1408
[73] Olfati-Saber R, Murray R M. Consensus problems in networks of agents with switchingtopology and time-delays [J]. IEEE Trans Automatic Control,2004,49(9):1520-1533
[74] Jadbabaie A, Lin J, Morse A. S. Coordination of groups of mobile autonomous agentsusing nearest neighbor rules [J]. IEEE Trans Automatic Control,2003,48(6):988-1001
[75] Fax J A, Murray R M. Information flow and cooperative control of vehicle formation [J].IEEE Trans Automatic Control,2004,49(9):1465-1476
[76] Lin J, Morse A. S, Anderson B D O. The multi-agent rendezvous problem [C]. Proc ofCDC, Maui, Hawaii,2003:1508-1513
[77] D M Lane, A G Mcfadzean. Distributed problem solving and real-time mechanisms inrobot architectures [J], Engineering Application Intelligence,1994,7(2):105-117
[78] G Cohen. Concurrent system to resolve real-time conflicts in multi-robot systems [J],Engineering Application Artificial Intelligence,1995,8(2):169-175
[79] B Burmeister, A Haddadi, G Maty lis. Applications of multi-agent systems in traffic andtransportation [J].IEEE Trans on Software Engineering,1997,144(1):51-60
[80] G Adorni, A Poggl. Route guidance as a just-in-time multi-agent task [J], AppliedArtificial Intelligence,1996,10(2):95-120
[81] K H Funk, J H Lind. Agent-based pilot-vehicle interfaces: Concept and prototype [J].IEEE Trans on Systems, Man and Cybernetics,1992,22(6):1309-1322
[82] G Vernazza, R Zunino. A distributed intelligence methodology for railway traffic control[J]. IEEE Trans on Vehicular Technology,1990,39(3):263-270
[83] C Ramos. Architecture and a negotiation protocol for the dynamic scheduling ofmanufacturing systems [A].IEEE Int Conf on Robotics and Automation [C]. USA,1994:3161-3166
[84] H V D Parunak. Distributed AI and manufacturing control: Some issues and insights [J].Proc1st European Workshop on Modeling an Autonomous Agent in a Multi-agent World
[C]. U K,1989:30-37
[85] Jennings N R, L Z Varga, R P Aarnts, et al. Transforming standalone expert systems intoa community of cooperating agents [J]. Engineering Application Artificial Intelligence,1993,6(4):317-331
[86] F Polat, S Shekhar, H A Guvenir. Distributed conflict resolution among cooperatingexpert systems [J], Expert Systems,1993,10(4):227-236
[87] Jennings N R. controlling cooperative problem solving in industrial multi-agent systemsusing joint intentions [J]. Artificial Intelligence,1995,75(2):195-240
[88] B C Draa, P Millot. A framework for cooperative work: An approach based on theintentionality [J]. Artificial Intelligence in Engineering,1990,5(4):199-205
[89] G Hartvigsen, D Johansen. Cooperation in a distributed artificial intelligenceenvironment-The storm cast application [J]. Engineering Application of ArtificialIntelligence,1990,3(3):229-237
[90] S J Russell. Provably bounded optimal agents [C], Proc of the13th Int Joint ConfoundArtificial Intelligence. USA,1993:40-48
[91] H Wang, C Wang. APACS: A multi-agent system with repository support [J]. Knowledge-based Systems,1996,9(3):329-337
[92]张安慧,张世杰,陈健等.多智能体系统可控性的图论刻画[J],控制与决策,2011,11:1621-1626
[93]傅朝阳.面向实时任务求解的自治服务协同模型、形式语义及其验证[D],浙江大学,2010
[94]史忠植.智能主体及其应用[M].北京：科学出版社，2000
[95]何炎祥，陈莘萌. Agent和多Agent系统的设计与应用[M],武汉：武汉大学出版社，2001
[96]冯培恩,钱仲焱,潘双夏等.基于AGENT架构的结构静动态协同优化方法研究[J].中国科学(E辑),2001,6(3):245~253
[97] Minsky M. The Society of Mind [M], New York: Simon and Schuster,1986
[98]张庆杰,沈林成,朱华勇.多智能体系统实现鲁棒一致的时延相关稳定判据[J],控制与决策,2012,27(4):584-591
[99]刘佳,陈增强,刘忠信.多智能体系统及其协同控制研究进展[J],智能系统学报.2010,5(1):1-7
[100]Xiaoyuan Luo, Nani Han, Xinping Guan.Leader-following consensus protocols forformation control of multi-agent network [J], Journal of systems engineering andelectronics.2011,22(6):991-997
[101]Zhihai Wu, Huajing Fang. Improvement for consens performance of multi-agentsystems based on delayed-state-derivative feedback [J], Journal of systems engineeringand electronics.2012,23(1):137-144
[102]Yingying She, Huangjing Fang. Fast consensus seeking for multi-agent systems[J],Journal of systems engineering and electronics.2011,22(3):534-539
[103]WANG Jing, NIAN Xiaohong, WANG Haibo. Consensus and formation control ofdiscrete-time multi-agent systems [J]. J. Cent. South Univ. Technol.2011.18:1161-1168
[104]Ren W, Beard R W. Distributed Consensus in Multi-Vehicle Cooperative Control,Theory and Applications [M]. Berlin: Springer,2008
[105]严卫生,李俊兵,王银涛.受损多智能体系统信息一致性[J].自动化学报,2012,38(11):1880-1884
[106]Huang Qin-zhen. Consensus analysis of multi-agent discretetime systems [J], Actaautomatica sinica,2012,38(7):1127-1133
[107]Yan Jing, Guan Xin-Ping, Luo xiao-Yuan, et al. Consensus and trajectory planning withinput constraints for multi-agent systems [J], Acta automatic sinica,2012,38(7):1074-1082
[108]杨洪勇,曹科才,张嗣瀛.具有领航者的时延多智能体系统的群集运动[J].计算机研究与发展.2011,48(2):203-208
[109]Cortés J. Distributed algorithms for reaching consensus on general functions [J],Automatic Control,2008,44(3):726-737
[110]Hong Y, Chen G, Bushnell L. Distributed observers design for leader-following controlof multi-agent networks [J]. Automatic Control,2008,44:846-850
[111]洪奕光,翟超.多智能体系统动态协调与分布式控制设计[J],控制理论与应用.2011,28(10):1506-1512
[112]Hong Y, Hu J, Gao L. Tracking control for multi-agent consensus with an active leaderand variable topology [J]. Automatica,2006,42(7):1177-1182.
[113]Fan Y S, Cao J W. Multi-Agent Systems: Theory, Method and Applications [J]. Belin:Springer-Verlag Heidelberg,2002
[114]石纯一，张伟，徐晋晖.多Agent系统引论[M].北京：电子工业出版社,2003
[115]刘大有,杨鲲,陈建中. Agent研究现状与发展趋势[J].软件学报,2000,11(3):315-321
[116]钟掘,胡志刚.基于耦合问题的多智能体主体协作模型[J],中南工业大学学报.1998,29(2):165-167
[117]刘金琨,王树青.多智能体控制系统的设计与实现[J].控制理论与应用,1999,16(4):580-582
[118]Li JX, Mao XJ, Shu Y. An object-oriented design model of software Agent[J], Journalof Software,2007,18(3):582-591
[119]Noy N F, Hafner C D. The state of the art in ontology design [J]. AI Magazine,1997,18(3):53~74
[120]Chandrasekaran B, Josephson J R, Benjamins V R. What are ontologies, and why do weneed them [J], IEEE Intelligent Systems&Their Applications,1999,14(1):20~26
[121]Fadel F G, Fox M S, Gruninger M. A generic enterprise resource ontology [J]. In: IEEEProceedings of the3rd Workshop on Enabling Technologies: Infrastructure forCollaborative Enterprise,1994.117~128
[122]陆汝钤,石纯一,张松懋等.面向Agent的常识知识库[J],中国科学（E辑）,2000,30(5):453-452
[123]DEAN Jones. Methodologies for ontology development [J],http://www.iet.com/project/RKF/SME,1999
[124]陆汝钤.世纪之交的知识工程与知识科学[M].北京:清华大学出版社,2001,450-451
[125]罗杰文,史忠植,王茂光等.基于动态描述逻辑的多主体协作模型[J],计算机研究与发展.2006,43(8):1317-1322
[126]杨善林,胡小建,马溪骏. DIDSS环境下信息Agent任务规范的分解[J].系统工程学报,2004,19(5):489-495
[127]Smith Reid G. The contract net Protocol: high-level communication and control in adistributed Problem solver [J].IEEE Transaction on Computes，1980，Vol.C-29，No.12:1104-1113
[128]Eugenio Oliveiro, Klaus Fischer. Multi Agent systems: which research for whichapplicat ions [J], Robotics and Autonomous Systems,1999(27):91-106
[129]Pietro Baroni, Daniela Fogli. Modeling, robot cognitive activity through active mentalentities [J], Robotics and Autonomous Systems,2000(30):325-349
[130]Jacques Ferber. Mult I Agent systems [M], Addison Wesley,1999
[131]Jacques Ferver. Multi agent systems: an introduction to distributed artificial intelligence
[M]. Harlow: Addison Wesley Longman,1999
[132]LI Hongjie, HUANG Qingxue, GONG Xiulian, et al. Research on Automatic TrackingTechnology and Improvement Model of Plate in Leveling Region [J]. AdvancedMaterials Research,2011,145(2011):404-409
[133]刘相华,胡贤磊,杜林秀等.轧制参数计算模型及其应用[M].化学工业出版社.北京:2007.7
[134]王昭东,田勇,赵忠等.中厚板厚度控制模型的自学习[J].东北大学学报(自然科学版),2006,27(7):771-775
[135]赵卫东,陈国华,盛昭瀚.基于智能Agent的复合学习方法[J],系统工程理论与实践.2002(12):61-67
[136]张贵军,柴天佑,张化光.基于专家系统的智能控制的研究现状及发展方向[J].东北大学学报（自然科学版）.1995,16(5):495-499
[137]周永林,潘云鹤.面向Agent的分析与建模[J].计算机研究与发展.1999,36(4):410-416
[138]陆汝钤,金芝,陈刚.面向本体的需求分析[J].软件学报,2000,11(8):1009-1017
[139]Deloach S A. Multi agent Systems Engineering a Methodology and Language forDesigning Agent Systems[C]. In: Proc of Agent Oriented Information Systems.1999:45-57
[140]Wagner G, Agent-Object-Relationship Modeling[C], In: Proc of Second InternationalSymposium-from Agent theory to Agent Implementation together,2000-04
[141]Wooldridge M, Jennings NR, Kinny D, The Gaia methodology for Agent-orientedanalysis and design [J], Int’l Journal of Autonomous Agents and Multi-Agent System,2000,3(3):285-312
[142]韩贺永,黄庆学,马立峰等.液压滚切剪液压系统的研究[J],四川大学学报(工程科学版),2011,43(3):239-243
[143]王毅,周兴社,韩兆轩.分布式实时控制系统执行软件的研究与设计[J].航空学报.1990,11(8):348-353
[144]刘家红,吴泉源.一个基于事件驱动的面向服务计算平台[J].计算机学报.2008.31(4):588-598
[145]矫志杰,何纯玉,陈波等.首钢中厚板轧机过程控制系统[J].东北大学学报(自然科学版).2004,25(5):412-415
[146]李家栋,李勇,王昭东等.中厚板加热过程在线控制应用软件的开发[J].东北大学学报(自然科学版),2010,31(8):1108-1112
[147]Microsoft SQL Server2000Help System
[148]LI Hongjie, HUANG Qingxue, JU Changjiang, et al. Research on rolling force model ofcomposite plate based on distributed cooperative control system [J], Applied Mechanicsand Materials.2013,299(2013):93-96
[149]山西省轧制工程中心、太原科大重工科技有限责任公司2300mm液压剪说明书
[2]黄庆学,马立峰,李进宝等.新型滚切剪非对称曲柄机构原理[J],机械工程学报,2008,44(5):119-123
[3]马立峰,黄庆学等.新型滚切剪空间剪切机构优化数学模型的建立及应用[J],四川大学学报（工程科学版）,2008,40(2):170-174
[4]楚志兵,黄庆学,马立峰等.滚切式双边剪连杆机构的动力学仿真及实验研究[J],四川大学学报(工程科学版),2011,43(1):247-251
[5]李玉贵,马立峰,黄庆学.单轴双偏心非对称负偏置滚切剪研究[J],钢铁,2008,43(2):51-55
[6] LI Hongjie, HUANG Qingxue, JU CHangjiang, et al. Research and application ofmulti-embedded system cooperative control for plate leveler [J]. ICIC Express Letters,2011,2(6):1321-1327
[7] Gui H L, Huang Q X, Chen Y M. Analysis of the contact problems using mixed fastmulti-pole boundary element method [J], ICIC Express Letters,2010,4(3):1281-1285
[8]王效岗,黄庆学,胡鹰.中厚板辊式矫直过程模型算法修正与应用[J],中国机械工程,2012,23(3):335-338
[9]韩贺永,黄庆学,张洪等.液压矫直机液压伺服系统动态特性分析比较[J].吉林大学学报（工学版）,2012,42(2):372-376
[10]孙一康.适用于轧钢过程的计算机控制系统[J].中国工程科学,2000,.2(1):73-76
[11]孙增圻.计算机控制理论与应用（第二版）[M].北京:清华大学出版社,2008
[12]彭天乾.过程计算机控制系统的性能评价[J].冶金自动化,1986,5:2-9
[13]周希德.控制理论与计算机实时控制[J].北方交通大学学报,1988,1:81-88
[14]阳宪惠.现场总线技术及其应用[M].北京:清华大学出版社,1999
[15] J P Thomesse. A review of the fieldbuses, Aeviews in Control [J],1998,22:35-45
[16] T Blevins, W Wojsznis. Fieldbus Support for Process Analysis [J], ISA Transactions,1996,35(2):177-183
[17]胡学林.可编程控制器原理及应用[M].北京:电子工业出版社,2012
[18]孙优贤.我国工业过程自动化高技术产业化重大进展[J].控制工程,2003,10(2):97-105
[19]郑申白,史东日,马劲红.轧制过程自动化技术[M].北京,化学工业出版社,2009
[20]朱亚斌,沈康.宝钢冷轧3级控制系统L3_L2_L1间通讯实现[J].南京理工大学学报,2005,29(10):199-202
[21]黄天煌.从霍尼韦尔DCS的变迁看过程自动化控制系统的发展趋势[J].自动化博览.2008.S1:30-34
[22]刘复华. TDCS:当代微机控制系统的发展方向[J].武汉工业大学学报.1988.NO.2:263-270
[23]张殿华,王国栋,王君等.四机架热连轧机分布式计算机控制系统[J].冶金自动化,1998.2:9-12
[24]孙一康.冷热轧板带轧机的模型与控制[M].北京:冶金工业出版社,2010
[25]刘玠,孙一康.带钢热连轧计算机控制[M].北京:机械工业出版社,1997
[26]王英,张小真, CSCW协同建组协商策略研究[J].计算机应用,2005,25(3):695-699
[27]魏力,陈昊,李凌等. CSCW中可靠有序的群组通信算法[J].电子科技,2009,22(1):55-59
[28]张志勇,杨林,马建峰等.基于可信计算的CSCW系统访问控制[J].华中科技大学学报(自然科学版),2008,36(1):59-62
[29]高胜,吴林.基于CSCW的遥控焊接机器人系统协同工作模型[J].焊接学报,2007,28(3):9-13
[30]胡斌,陈刚,董金祥.一种用于CSCW系统设计的认知模型[J].计算机工程,2004,30(13):133-135
[31]肖波,张东,诸鸿文.计算机支持的协同工作并发控制策略[J].上海交通大学学报,1999,33(1):101-104
[32]宋海刚,陈学广.计算机支持的协同工作发展述评[J].计算机工程与应用,2004,1:7-11
[33]王国意,史元春,徐光佑.计算机支持的协同工作系统的时序逻辑模型[J],软件学报,1998,9(3):169-173
[34]刘立骐,田华,许维胜等. CSCW研究理论及应用[J].信息与控制,1998, Vol.27,No.3:190-193
[35] Walter Reinhard, Jean Svhweizer, Gerd Volksen, et al. CSCW: Concepts andArchitectures [J]. IEEE Computers,1994,27(5):28-36
[36]王晓丽,洪奕光.多智能体系统分布式控制的研究新进展[J].复杂系统与复杂性科学.2010, Vol.7, No.2-3:70-81
[37]刘金琨,尔联洁.多智能体技术应用综述[J].控制与决策,2001,Vol.16, No.2:133-139
[38]毛新军.面向主体的软件开发[M],北京:清华大学出版社.2005
[39]毛新军,常志明,王戟等.面向Agent的软件工程:现状与挑战[J],计算机研究与发展.2006,43(10):1782-1789
[40] Gerhard Weib. Agent orientation in software engineering [J], The KnowledgeEngineering Review,2001,16(4):349-373
[41] Mao Xinjun, Wang Ji, Chen Jiajia. Modeling the organization structure of multi-agentsystem [C], IAT’2005, Compiegne, France,2005
[42] Michael Wooldridge, Paolo Ciancarini. Agent-oriented software engineering: The state ofthe art [G], In: Proc of AOSE’2001, LNAI1957. Berlin: Springer,2001
[43] Ofer Arazy, Carson C Woo. Analysis and design of agent-oriented information systems[J], The Knowledge Engineering Review,2002,17(3):215-260
[44] K H Dam, M Winikoff. Comparing agent-oriented methodologies [C], The5th Int’lBi-Conference Workshop on Agent-Oriented Information System, Melbourne,2003
[45] Qi Yan, Xinjun Mao, Hong Zhu, et al. Modeling multi-agent system with soft genes,roles and agents [G], In: Proc of AOSE’2004, LNCS3382. Springer,2004.231-245
[46] Yoav Shoham. Agent-oriented programming [J], Artificial Intelligence,1993,60(1):51-92
[47] R H Bordini, M Dastani, J Dix, et al. Programming multi-agent systems [C], Proc of2ndInt’l Workshop ProMAS. Berlin: Springer,2004
[48] Stefan Bussmann, Nicholas R Jennings, Michael Wooldridge, Reuse of interactionprotocols for agent-based control applications [C], In: Proc of AOSE’2002, LNCS2585.Berlin: Springer,2002:73-87
[49] J A Giampapa, O H JuarezEspinosa, K P Sycara, Configuration management formulti-agent systems [C], In: Proc of AGENT2001. New York: ACM Press,2001:230-231
[50] H Zhu, L Shan. Caste-centric modelling of multi-agent systems: The CAMLE modellinglanguage and automated tools [G], In: Model-Driven Software Development, Researchand Pract ice in Software Engineering II. Berlin: Springer,2004
[51] H Zhu, A formal specification language for agent-oriented software engineering [C], In:Proc of AAMAS.2003, New York: ACM Press,2003:1174-1175
[52] A Fuxman, M Pistore, J Mylopoulos, et al. Model checking early requirementsspecifications in tropos [C], IEEE Int’1Sympon Requirements Engineering, Toronto,Canada,2001
[53] Jennings N R. On agent-based software engineering [J], Artificial Intelligence,2000,117(2):277-296
[54]蔡自兴,徐光祐.人工智能及其应用[M].北京:清华大学出版社,2004
[55] MAES P. Modeling adaptive autonomous Agent [J]. Artificial Life,1994,1(1/2):135-162
[56] Wooldrige M, Jennings N R. Intelligent Agents: theory and practice [J]. KnowledgeEngineering Review,1995,10(2):112-152
[57] Reynolds C W. Flocks, herds, and schools: a distributed behavioral model [J]. ComputerGraphics,1987,21:25-34
[58] Vicsek T, Cziro k A, Ben-Jacob E, et al. Novel type of phase transition in a system ofself-driven particles [J]. Phys Rev Letts,1995,75(6):1226-1229
[59] Couzin I D, Krause J, Franks N R, et al. Effective leadership and decision making inanimal groups on the move [J]. Nature,2005,433:513-516
[60] Olfati-Saber R. Flocking for multi-agent dynamic systems: algorithms and theory [J].IEEE Trans Automatic Control,2006,51:401-420
[61] Tanner H G, Jadbabaie A, Pappas G J. Flocking in fixed and switching networks [J].IEEE Transactions on Automatic Control,2007,52(5):863-868
[62] Casbeer D W, Kingston D B, Beard R W, et al. Cooperative forest re surveillance using ateam of small unmanned air vehicles [J]. International Journal of Systems Sciences,2006,37:351-360
[63] Gage D W. Command control for many-robot systems [C]. AUVS92, the NineteenthAnnual AUVS Technical Symposium. Huntsville, Alabama, USA,1992:22-24
[64] Ma C Q, Zhang J F. Necessary and sufficient conditions for consensus ability of linearmulti-agent systems [J]. IEEE Trans on Automatic Control,2010,55(10):1263-1268
[65] Lin Z, Francis B, Maggiore M. State agreement for continuous-time coupled nonlinearsystems [J]. SIAM Journal on Control and Optimization,2007,46(1):288-307
[66] Moreau L. Stability of multi-agent systems with time-dependent communication links [J].IEEE Transitions on Automatic Control,2005,50(2):169-182
[67] Lin P, Jia Y M. Average consensus in networks of multi-agents with both switchingtopology and coupling time-delay [J]. Physical A: Statistical Mechanics and itsApplications,2008,387(1):303-313
[68] Xin Z, Guo L. Synchronization of multi-agent systems without connectivity assumptions[J]. Automatic Control,2009,45(12):2744-2753
[69] Chen F, Chen Z Q, Xiang L Y, et al. reaching a consensus via pinning control [J].Automatic Control,2009,45(5):1215-1220
[70] LYNCH N A. Distributed Algorithms [M]. San Francisco, CA: Morgan Kaufmann,1997
[71] Hong Y, GAO L, CHENG D, et al. Lyapuov-based approach to multi-agent systems withswitching jointly connected interconnection [J]. IEEE transactions on automatic control,2007,52(5):943-948
[72] Y C P Jeff, J M Tenenbaum. An intelligent agent framework for enterprise integration [J],IEEE Transon systems, Man and Cybernetics,1991,21(6):1391-1408
[73] Olfati-Saber R, Murray R M. Consensus problems in networks of agents with switchingtopology and time-delays [J]. IEEE Trans Automatic Control,2004,49(9):1520-1533
[74] Jadbabaie A, Lin J, Morse A. S. Coordination of groups of mobile autonomous agentsusing nearest neighbor rules [J]. IEEE Trans Automatic Control,2003,48(6):988-1001
[75] Fax J A, Murray R M. Information flow and cooperative control of vehicle formation [J].IEEE Trans Automatic Control,2004,49(9):1465-1476
[76] Lin J, Morse A. S, Anderson B D O. The multi-agent rendezvous problem [C]. Proc ofCDC, Maui, Hawaii,2003:1508-1513
[77] D M Lane, A G Mcfadzean. Distributed problem solving and real-time mechanisms inrobot architectures [J], Engineering Application Intelligence,1994,7(2):105-117
[78] G Cohen. Concurrent system to resolve real-time conflicts in multi-robot systems [J],Engineering Application Artificial Intelligence,1995,8(2):169-175
[79] B Burmeister, A Haddadi, G Maty lis. Applications of multi-agent systems in traffic andtransportation [J].IEEE Trans on Software Engineering,1997,144(1):51-60
[80] G Adorni, A Poggl. Route guidance as a just-in-time multi-agent task [J], AppliedArtificial Intelligence,1996,10(2):95-120
[81] K H Funk, J H Lind. Agent-based pilot-vehicle interfaces: Concept and prototype [J].IEEE Trans on Systems, Man and Cybernetics,1992,22(6):1309-1322
[82] G Vernazza, R Zunino. A distributed intelligence methodology for railway traffic control[J]. IEEE Trans on Vehicular Technology,1990,39(3):263-270
[83] C Ramos. Architecture and a negotiation protocol for the dynamic scheduling ofmanufacturing systems [A].IEEE Int Conf on Robotics and Automation [C]. USA,1994:3161-3166
[84] H V D Parunak. Distributed AI and manufacturing control: Some issues and insights [J].Proc1st European Workshop on Modeling an Autonomous Agent in a Multi-agent World
[C]. U K,1989:30-37
[85] Jennings N R, L Z Varga, R P Aarnts, et al. Transforming standalone expert systems intoa community of cooperating agents [J]. Engineering Application Artificial Intelligence,1993,6(4):317-331
[86] F Polat, S Shekhar, H A Guvenir. Distributed conflict resolution among cooperatingexpert systems [J], Expert Systems,1993,10(4):227-236
[87] Jennings N R. controlling cooperative problem solving in industrial multi-agent systemsusing joint intentions [J]. Artificial Intelligence,1995,75(2):195-240
[88] B C Draa, P Millot. A framework for cooperative work: An approach based on theintentionality [J]. Artificial Intelligence in Engineering,1990,5(4):199-205
[89] G Hartvigsen, D Johansen. Cooperation in a distributed artificial intelligenceenvironment-The storm cast application [J]. Engineering Application of ArtificialIntelligence,1990,3(3):229-237
[90] S J Russell. Provably bounded optimal agents [C], Proc of the13th Int Joint ConfoundArtificial Intelligence. USA,1993:40-48
[91] H Wang, C Wang. APACS: A multi-agent system with repository support [J]. Knowledge-based Systems,1996,9(3):329-337
[92]张安慧,张世杰,陈健等.多智能体系统可控性的图论刻画[J],控制与决策,2011,11:1621-1626
[93]傅朝阳.面向实时任务求解的自治服务协同模型、形式语义及其验证[D],浙江大学,2010
[94]史忠植.智能主体及其应用[M].北京：科学出版社，2000
[95]何炎祥，陈莘萌. Agent和多Agent系统的设计与应用[M],武汉：武汉大学出版社，2001
[96]冯培恩,钱仲焱,潘双夏等.基于AGENT架构的结构静动态协同优化方法研究[J].中国科学(E辑),2001,6(3):245~253
[97] Minsky M. The Society of Mind [M], New York: Simon and Schuster,1986
[98]张庆杰,沈林成,朱华勇.多智能体系统实现鲁棒一致的时延相关稳定判据[J],控制与决策,2012,27(4):584-591
[99]刘佳,陈增强,刘忠信.多智能体系统及其协同控制研究进展[J],智能系统学报.2010,5(1):1-7
[100]Xiaoyuan Luo, Nani Han, Xinping Guan.Leader-following consensus protocols forformation control of multi-agent network [J], Journal of systems engineering andelectronics.2011,22(6):991-997
[101]Zhihai Wu, Huajing Fang. Improvement for consens performance of multi-agentsystems based on delayed-state-derivative feedback [J], Journal of systems engineeringand electronics.2012,23(1):137-144
[102]Yingying She, Huangjing Fang. Fast consensus seeking for multi-agent systems[J],Journal of systems engineering and electronics.2011,22(3):534-539
[103]WANG Jing, NIAN Xiaohong, WANG Haibo. Consensus and formation control ofdiscrete-time multi-agent systems [J]. J. Cent. South Univ. Technol.2011.18:1161-1168
[104]Ren W, Beard R W. Distributed Consensus in Multi-Vehicle Cooperative Control,Theory and Applications [M]. Berlin: Springer,2008
[105]严卫生,李俊兵,王银涛.受损多智能体系统信息一致性[J].自动化学报,2012,38(11):1880-1884
[106]Huang Qin-zhen. Consensus analysis of multi-agent discretetime systems [J], Actaautomatica sinica,2012,38(7):1127-1133
[107]Yan Jing, Guan Xin-Ping, Luo xiao-Yuan, et al. Consensus and trajectory planning withinput constraints for multi-agent systems [J], Acta automatic sinica,2012,38(7):1074-1082
[108]杨洪勇,曹科才,张嗣瀛.具有领航者的时延多智能体系统的群集运动[J].计算机研究与发展.2011,48(2):203-208
[109]Cortés J. Distributed algorithms for reaching consensus on general functions [J],Automatic Control,2008,44(3):726-737
[110]Hong Y, Chen G, Bushnell L. Distributed observers design for leader-following controlof multi-agent networks [J]. Automatic Control,2008,44:846-850
[111]洪奕光,翟超.多智能体系统动态协调与分布式控制设计[J],控制理论与应用.2011,28(10):1506-1512
[112]Hong Y, Hu J, Gao L. Tracking control for multi-agent consensus with an active leaderand variable topology [J]. Automatica,2006,42(7):1177-1182.
[113]Fan Y S, Cao J W. Multi-Agent Systems: Theory, Method and Applications [J]. Belin:Springer-Verlag Heidelberg,2002
[114]石纯一，张伟，徐晋晖.多Agent系统引论[M].北京：电子工业出版社,2003
[115]刘大有,杨鲲,陈建中. Agent研究现状与发展趋势[J].软件学报,2000,11(3):315-321
[116]钟掘,胡志刚.基于耦合问题的多智能体主体协作模型[J],中南工业大学学报.1998,29(2):165-167
[117]刘金琨,王树青.多智能体控制系统的设计与实现[J].控制理论与应用,1999,16(4):580-582
[118]Li JX, Mao XJ, Shu Y. An object-oriented design model of software Agent[J], Journalof Software,2007,18(3):582-591
[119]Noy N F, Hafner C D. The state of the art in ontology design [J]. AI Magazine,1997,18(3):53~74
[120]Chandrasekaran B, Josephson J R, Benjamins V R. What are ontologies, and why do weneed them [J], IEEE Intelligent Systems&Their Applications,1999,14(1):20~26
[121]Fadel F G, Fox M S, Gruninger M. A generic enterprise resource ontology [J]. In: IEEEProceedings of the3rd Workshop on Enabling Technologies: Infrastructure forCollaborative Enterprise,1994.117~128
[122]陆汝钤,石纯一,张松懋等.面向Agent的常识知识库[J],中国科学（E辑）,2000,30(5):453-452
[123]DEAN Jones. Methodologies for ontology development [J],http://www.iet.com/project/RKF/SME,1999
[124]陆汝钤.世纪之交的知识工程与知识科学[M].北京:清华大学出版社,2001,450-451
[125]罗杰文,史忠植,王茂光等.基于动态描述逻辑的多主体协作模型[J],计算机研究与发展.2006,43(8):1317-1322
[126]杨善林,胡小建,马溪骏. DIDSS环境下信息Agent任务规范的分解[J].系统工程学报,2004,19(5):489-495
[127]Smith Reid G. The contract net Protocol: high-level communication and control in adistributed Problem solver [J].IEEE Transaction on Computes，1980，Vol.C-29，No.12:1104-1113
[128]Eugenio Oliveiro, Klaus Fischer. Multi Agent systems: which research for whichapplicat ions [J], Robotics and Autonomous Systems,1999(27):91-106
[129]Pietro Baroni, Daniela Fogli. Modeling, robot cognitive activity through active mentalentities [J], Robotics and Autonomous Systems,2000(30):325-349
[130]Jacques Ferber. Mult I Agent systems [M], Addison Wesley,1999
[131]Jacques Ferver. Multi agent systems: an introduction to distributed artificial intelligence
[M]. Harlow: Addison Wesley Longman,1999
[132]LI Hongjie, HUANG Qingxue, GONG Xiulian, et al. Research on Automatic TrackingTechnology and Improvement Model of Plate in Leveling Region [J]. AdvancedMaterials Research,2011,145(2011):404-409
[133]刘相华,胡贤磊,杜林秀等.轧制参数计算模型及其应用[M].化学工业出版社.北京:2007.7
[134]王昭东,田勇,赵忠等.中厚板厚度控制模型的自学习[J].东北大学学报(自然科学版),2006,27(7):771-775
[135]赵卫东,陈国华,盛昭瀚.基于智能Agent的复合学习方法[J],系统工程理论与实践.2002(12):61-67
[136]张贵军,柴天佑,张化光.基于专家系统的智能控制的研究现状及发展方向[J].东北大学学报（自然科学版）.1995,16(5):495-499
[137]周永林,潘云鹤.面向Agent的分析与建模[J].计算机研究与发展.1999,36(4):410-416
[138]陆汝钤,金芝,陈刚.面向本体的需求分析[J].软件学报,2000,11(8):1009-1017
[139]Deloach S A. Multi agent Systems Engineering a Methodology and Language forDesigning Agent Systems[C]. In: Proc of Agent Oriented Information Systems.1999:45-57
[140]Wagner G, Agent-Object-Relationship Modeling[C], In: Proc of Second InternationalSymposium-from Agent theory to Agent Implementation together,2000-04
[141]Wooldridge M, Jennings NR, Kinny D, The Gaia methodology for Agent-orientedanalysis and design [J], Int’l Journal of Autonomous Agents and Multi-Agent System,2000,3(3):285-312
[142]韩贺永,黄庆学,马立峰等.液压滚切剪液压系统的研究[J],四川大学学报(工程科学版),2011,43(3):239-243
[143]王毅,周兴社,韩兆轩.分布式实时控制系统执行软件的研究与设计[J].航空学报.1990,11(8):348-353
[144]刘家红,吴泉源.一个基于事件驱动的面向服务计算平台[J].计算机学报.2008.31(4):588-598
[145]矫志杰,何纯玉,陈波等.首钢中厚板轧机过程控制系统[J].东北大学学报(自然科学版).2004,25(5):412-415
[146]李家栋,李勇,王昭东等.中厚板加热过程在线控制应用软件的开发[J].东北大学学报(自然科学版),2010,31(8):1108-1112
[147]Microsoft SQL Server2000Help System
[148]LI Hongjie, HUANG Qingxue, JU Changjiang, et al. Research on rolling force model ofcomposite plate based on distributed cooperative control system [J], Applied Mechanicsand Materials.2013,299(2013):93-96
[149]山西省轧制工程中心、太原科大重工科技有限责任公司2300mm液压剪说明书