分布式自组织顺序控制系统的研究与应用
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摘要
随着工业生产规模的扩大以及复杂度的增加,越来越多的控制系统采用分布式的结构,而且近些年来,无线技术在工业领域的应用范围也在不断扩大。在这两种发展趋势下,本文提出分布式自组织顺序控制系统(Distributed Self-organization Sequence Control System,DSSCS),并对其展开深入的探讨和研究。DSSCS利用无线节点的计算、存储和通信资源,以分布式的方式执行顺序控制逻辑,而且能够自动生成控制逻辑,提高了系统的自动化水平,对推动工业自动化的发展具有积极意义。
本文中的DSSCS以无线网络为基础,无线传输中的延时和误码会导致系统产生完全错误的控制指令,造成严重后果。因此,需要设计相应的机制降低延时和误码造成的影响,而且还要保证系统的能控性和能稳定性。此外,传统组态方式效率较低而且容易出错,为了提高DSSCS的组态效率,设计一种面向生产过程的控制逻辑自组织生成方式。围绕上述DSSCS实现过程中的关键问题,本文取得如下的理论研究成果和创新点：
1.提出了分布式自组织顺序控制系统(DSSCS)。DSSCS没有集中的控制器,控制逻辑完全分散到现场的无线控制节点上,以分布式的方式完成系统的控制任务。此外,系统还能以自组织方式生成控制逻辑,从而无需人工组态就能够自动生成控制逻辑。与传统的顺序控制系统相比,DSSCS具有明显的优点：分布式的系统结构消除了集中故障；使用无线网络传输现场信号节约了大量的线缆；控制逻辑的自组织生成方式提高了组态效率。
2.分析无线传输中的延时和误码对DSSCS性能的影响,并设计降低影响的机制。利用确定与随机Petri网和时序Petri网,并引入复合标识对系统进行建模,用随机时间变迁表示无线传输延时,用冲突变迁之间的概率触发表示误码的发生,同时引入时序逻辑公式确定DSSCS中其余冲突变迁的触发条件,使系统能够按照指定的步序进行状态转移。通过建立的模型,分析系统可能出现的状态及其持续时间,判定系统的运行过程是否符合步序要求。针对传输中的误码提出状态限定的方法提高系统正确运行的概率,同时采用偏差补偿方法减小由无线传输延时造成的状态持续时间偏差,并通过仿真试验证明方法的有效性。
3.利用布尔控制网络建立DSSCS的控制模型,并引入半张量积得到系统的状态关联矩阵,分析误码和延时对DSSCS能控性和能稳定性的影响。分析过程中,将误码导致传输状态的改变转化为控制节点选择不同的结构矩阵,从而得到不同的系统状态关联矩阵,并且将带延时的系统状态,根据延时的不同分解为不同的状态转移路径。基于系统可能出现的状态关联矩阵以及最长路径的长度,得到DSSCS在误码和延时影响下的能控性和能稳定性判据。在使用半张量积的同时,提出面向生产过程的控制逻辑自组织生成方式,通过面向生产过程的操作,使分散的控制节点自动确定表示控制逻辑的结构矩阵,形成一个有组织、协同控制的顺序控制系统,而且在更换无线节点的过程中,系统也能对分布式控制逻辑进行自动维护。
4.在电站化学水处理车间内超滤系统的顺序控制中实现基于无线网络的DSSCS。根据实际生产的要求,构建系统的整体框架,设计无线网络信息共享、控制逻辑自组织生成、分散控制、分层诊断、实时监测功能,并兼顾无线网络的低功耗设计,实现安全、可靠、低功耗的DSSCS。同时,给出无线DI/O模块、基站的软硬件设计原理,并展示了DSSCS在现场的应用情况。
As the expansion of the scale and the growth of the complexity of industrial production, the distributed structure is adopted in more and more control system. Besides that, the scale of the application of wireless technology in industrial field has been enlarged constantly in recent years. Given these trends, a distributed self-organization sequence control system (DSSCS) is proposed and discussions and research are carried out in-depth. In DSSCS, the resource of computation, memory and communication is utilized to not only execute the sequence control logic in a distributed manner, but also generate the control logic automatically. It improves the level of automation of the system and bears positive significance for the development of industrial automation.
For the realization of DSSCS is based on wireless network, the delay and bit error in wireless transmission may lead the system to generating totally wrong control command, resulting in serious consequences. So related mechanisms have to be designed to reduce the influence caused by delay and bit error and the controllability and stabilizability of the system should be also guaranteed. In addition, for the traditional manner of configuration is of inefficiency and fallibility, to improve the configuration efficiency of DSSCS, the generation of control logic in self-organization manner which is production-oriented is designed. Around the above critical problems in the realization of DSSCS, the theoretical research results and innovative points achieved in this paper are summarized as follows:
1. A Distributed Self-organization Sequence Control System (DSSCS) is proposed. There is no centralized controller in DSSCS and the control logic is totally dispersed into the wireless control nodes in field, executing the control tasks in a distributed manner. Besides that, the system can generate the control logic in a self-organization manner, so that the control logic can be generated automatically without artificial configuration. Compared to the traditional sequence control system, DSSCS has distinct advantage, such as the centralized fault is eliminated by adopting distributed structure, lots of cable is saved by using wireless network for signal transmission and the configuration efficiency is improved through the manner of self-organized generation of control logic.
2. Analyzing the performance of DSSCS affected by delay and bit error in wireless transmission and designing the mechanisms reducing the influence. The deterministic and stochastic Petri net and temporal Petri net are combined to model the work process of DSSCS with the complexed marking introduced. The delay in wireless transmission is presented by the transition with randomly distributed firing time and the occurrence of bit error is simulated by the probabilistic firing between the conflicted transitions. To make sure that the states of the system are transferred according to the given sequence steps, temporal logic equations are introduced to determine the firing condition of other conflicted transitions in DSSCS. Based on the derived model, the possible states and their durations can be analyzed, so that it can be confirmed whether the operation of the system meets the requirement of the given steps. Considering the bit error in transmission, the method of state restriction is proposed to improve the probability that the system operates correctly, meanwhile the deviation compensation is presented to minimize the deviation of the duration of the states. And the simulation results are also presented to show the improvement.
3. Using Boolean control network to build the control model of DSSCS, with semi-tensor product introduced, the state incidence matrix of the system is obtained to analyze the controllability and stabilizability of DSSCS affected by bit error and delay. In the analysis, the problem of the altered states caused by bit error is transformed as that the control nodes choose different structure matrices and different state incidence matrices of the system will be derived. And the system states with delay are decomposed into different state transition paths according to the value of delay. Based on the possible structure matrices and the length of the longest path, the criteria of the controllability and stabilizability of DSSCS affected by bit error and delay can be derived. Besides that, by using semi-tensor product, the self-organized generation of control logic which is production-oriented is proposed. So, the distributed control nodes can automatically generate the structure matrices which denote the corresponding control logics through the operation based on production process, forming an organized sequence control system with cooperative control. Moreover, the control nodes can automatically maintain the distributed control logics in the situation that the nodes are replaced.
4. DSSCS based on wireless network is applied for the sequence control of ultrafiltration system of chemical water treatment in power plant. According to the requirement of practical production, the overall framework is constructed and several functions are designed, such as information sharing, control logic generation in self-organized manner, distributed control, hierarchical diagnosis and real-time supervision with the low-power design for wireless network considered, to realize a DSSCS with safety, reliability and low-power dissipation. In addition, the design principles of the hardware and software of wireless DI/O modules and base station are presented. And the application of DSSCS in the field is exhibited.
本文中的DSSCS以无线网络为基础,无线传输中的延时和误码会导致系统产生完全错误的控制指令,造成严重后果。因此,需要设计相应的机制降低延时和误码造成的影响,而且还要保证系统的能控性和能稳定性。此外,传统组态方式效率较低而且容易出错,为了提高DSSCS的组态效率,设计一种面向生产过程的控制逻辑自组织生成方式。围绕上述DSSCS实现过程中的关键问题,本文取得如下的理论研究成果和创新点：
1.提出了分布式自组织顺序控制系统(DSSCS)。DSSCS没有集中的控制器,控制逻辑完全分散到现场的无线控制节点上,以分布式的方式完成系统的控制任务。此外,系统还能以自组织方式生成控制逻辑,从而无需人工组态就能够自动生成控制逻辑。与传统的顺序控制系统相比,DSSCS具有明显的优点：分布式的系统结构消除了集中故障；使用无线网络传输现场信号节约了大量的线缆；控制逻辑的自组织生成方式提高了组态效率。
2.分析无线传输中的延时和误码对DSSCS性能的影响,并设计降低影响的机制。利用确定与随机Petri网和时序Petri网,并引入复合标识对系统进行建模,用随机时间变迁表示无线传输延时,用冲突变迁之间的概率触发表示误码的发生,同时引入时序逻辑公式确定DSSCS中其余冲突变迁的触发条件,使系统能够按照指定的步序进行状态转移。通过建立的模型,分析系统可能出现的状态及其持续时间,判定系统的运行过程是否符合步序要求。针对传输中的误码提出状态限定的方法提高系统正确运行的概率,同时采用偏差补偿方法减小由无线传输延时造成的状态持续时间偏差,并通过仿真试验证明方法的有效性。
3.利用布尔控制网络建立DSSCS的控制模型,并引入半张量积得到系统的状态关联矩阵,分析误码和延时对DSSCS能控性和能稳定性的影响。分析过程中,将误码导致传输状态的改变转化为控制节点选择不同的结构矩阵,从而得到不同的系统状态关联矩阵,并且将带延时的系统状态,根据延时的不同分解为不同的状态转移路径。基于系统可能出现的状态关联矩阵以及最长路径的长度,得到DSSCS在误码和延时影响下的能控性和能稳定性判据。在使用半张量积的同时,提出面向生产过程的控制逻辑自组织生成方式,通过面向生产过程的操作,使分散的控制节点自动确定表示控制逻辑的结构矩阵,形成一个有组织、协同控制的顺序控制系统,而且在更换无线节点的过程中,系统也能对分布式控制逻辑进行自动维护。
4.在电站化学水处理车间内超滤系统的顺序控制中实现基于无线网络的DSSCS。根据实际生产的要求,构建系统的整体框架,设计无线网络信息共享、控制逻辑自组织生成、分散控制、分层诊断、实时监测功能,并兼顾无线网络的低功耗设计,实现安全、可靠、低功耗的DSSCS。同时,给出无线DI/O模块、基站的软硬件设计原理,并展示了DSSCS在现场的应用情况。
As the expansion of the scale and the growth of the complexity of industrial production, the distributed structure is adopted in more and more control system. Besides that, the scale of the application of wireless technology in industrial field has been enlarged constantly in recent years. Given these trends, a distributed self-organization sequence control system (DSSCS) is proposed and discussions and research are carried out in-depth. In DSSCS, the resource of computation, memory and communication is utilized to not only execute the sequence control logic in a distributed manner, but also generate the control logic automatically. It improves the level of automation of the system and bears positive significance for the development of industrial automation.
For the realization of DSSCS is based on wireless network, the delay and bit error in wireless transmission may lead the system to generating totally wrong control command, resulting in serious consequences. So related mechanisms have to be designed to reduce the influence caused by delay and bit error and the controllability and stabilizability of the system should be also guaranteed. In addition, for the traditional manner of configuration is of inefficiency and fallibility, to improve the configuration efficiency of DSSCS, the generation of control logic in self-organization manner which is production-oriented is designed. Around the above critical problems in the realization of DSSCS, the theoretical research results and innovative points achieved in this paper are summarized as follows:
1. A Distributed Self-organization Sequence Control System (DSSCS) is proposed. There is no centralized controller in DSSCS and the control logic is totally dispersed into the wireless control nodes in field, executing the control tasks in a distributed manner. Besides that, the system can generate the control logic in a self-organization manner, so that the control logic can be generated automatically without artificial configuration. Compared to the traditional sequence control system, DSSCS has distinct advantage, such as the centralized fault is eliminated by adopting distributed structure, lots of cable is saved by using wireless network for signal transmission and the configuration efficiency is improved through the manner of self-organized generation of control logic.
2. Analyzing the performance of DSSCS affected by delay and bit error in wireless transmission and designing the mechanisms reducing the influence. The deterministic and stochastic Petri net and temporal Petri net are combined to model the work process of DSSCS with the complexed marking introduced. The delay in wireless transmission is presented by the transition with randomly distributed firing time and the occurrence of bit error is simulated by the probabilistic firing between the conflicted transitions. To make sure that the states of the system are transferred according to the given sequence steps, temporal logic equations are introduced to determine the firing condition of other conflicted transitions in DSSCS. Based on the derived model, the possible states and their durations can be analyzed, so that it can be confirmed whether the operation of the system meets the requirement of the given steps. Considering the bit error in transmission, the method of state restriction is proposed to improve the probability that the system operates correctly, meanwhile the deviation compensation is presented to minimize the deviation of the duration of the states. And the simulation results are also presented to show the improvement.
3. Using Boolean control network to build the control model of DSSCS, with semi-tensor product introduced, the state incidence matrix of the system is obtained to analyze the controllability and stabilizability of DSSCS affected by bit error and delay. In the analysis, the problem of the altered states caused by bit error is transformed as that the control nodes choose different structure matrices and different state incidence matrices of the system will be derived. And the system states with delay are decomposed into different state transition paths according to the value of delay. Based on the possible structure matrices and the length of the longest path, the criteria of the controllability and stabilizability of DSSCS affected by bit error and delay can be derived. Besides that, by using semi-tensor product, the self-organized generation of control logic which is production-oriented is proposed. So, the distributed control nodes can automatically generate the structure matrices which denote the corresponding control logics through the operation based on production process, forming an organized sequence control system with cooperative control. Moreover, the control nodes can automatically maintain the distributed control logics in the situation that the nodes are replaced.
4. DSSCS based on wireless network is applied for the sequence control of ultrafiltration system of chemical water treatment in power plant. According to the requirement of practical production, the overall framework is constructed and several functions are designed, such as information sharing, control logic generation in self-organized manner, distributed control, hierarchical diagnosis and real-time supervision with the low-power design for wireless network considered, to realize a DSSCS with safety, reliability and low-power dissipation. In addition, the design principles of the hardware and software of wireless DI/O modules and base station are presented. And the application of DSSCS in the field is exhibited.
引文
[1]Ramsten A C, Saljo R. Communities, boundary practices and incentives for knowledge sharing?:A study of the deployment of a digital control system in a process industry as a learning activity [J]. Learning, Culture and Social Interaction, 2012,1(1):33-44.
[2]陈慧琴,蔡均.工业控制系统信息化发展综述[J].仪器仪表用户,2007,(14)1：1-2.
[3]张桢,牛玉刚.DCS与现场总线综述[J].电气自动化,2013,35(1)：4-6+46.
[4]Gungor V C, Hancke G P. Industrial wireless sensor networks:Challenges, design principles, and technical approaches [J]. Industrial Electronics, IEEE Transactions on, 2009,56(10):4258-4265.
[5]Low K S, Win W N N, Er M J. Wireless sensor networks for industrial environments [C]. Computational Intelligence for Modelling, Control and Automation,2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on. IEEE,2005,2:271-276.
[6]Andreas W. Recent and Emerging Topics in Wireless Industrial Communications:A Selection [J]. IEEE Transactions on Industrial Informatics,2008,4(2):102-124.
[7]白焰,吴鸿,杨国田.分散控制系统与现场总线控制系统——基础、评选、设计和应用[M].北京：中国电力出版社,2001.
[8]吕俊.分布式控制系统中的通信机制的研究[D].杭州：浙江大学,2003.
[9]刘向杰,彭一民.现场总线控制系统的现状与发展[J].电网技术,1999,23(3)：47-50.
[10]曹霖.分布式控制系统的设计与实现[D].南京：南京航空航天大学,2011.
[11]潘凤萍,陈世和,张红福等.1000MW超超临界机组自启停控制系统总体方案设计与应用[J].中国电力,2009,42(10)：15-18.
[12]王志祥,黄伟.热工保护与顺序控制[M].北京：中国电力出版社,2008.
[13]施玉晨.无线中继系统中的编码与协作传输技术研究[D].西安：西安电子科技大学,2012.
[14]王亚刚,许晓鸣,彭瑜等.无线传感器网络阀门检漏仪表的设计[J].自动化仪表,2010,31(4)：22-24.
[15]湛浩晏,孙长嵩,吴珊等.ZigBee技术在煤矿井下救援系统中的应用[J].计算机工程与应用,2006,42(24)：181-183.
[16]Song J, Han S, Mok A K, et al. WirelessHART:Applying wireless technology in real-time industrial process control [C]. Real-Time and Embedded Technology and Applications Symposium,2008. RTAS'08. IEEE. IEEE,2008:377-386.
[17]王平,刘其琛,王恒等.一种适用于ISA100.11a工业无线网络的通信调度方法[J].仪器仪表学报,2011,32(5)：1189-1195.
[18]刘扬,曾鹏,尚志军等.基于工业无线网络WIA技术的储油罐监测系统[J].仪器仪表标准化与计量,2009,05：20-21+24.
[19]曾鹏,王军.基于WIA技术的油井远程计量与优化控制系统[J].自动化博览,2010,02：18-20+30.
[20]王仁书,白焰,汪凤珠等.无线监控系统在电站化学水处理超滤系统中的应用[J].中国电力,2012,45(07)：84-88.
[21]王仁书,白焰,李秋灵等。基于无线传输顺控系统的超滤系统性能分析与仿真[J].系统仿真学报,2014,26(1)：23-28.
[22]白焰,王仁书,汪凤珠等.一种基于无线网络的分布式自学习顺序控制系统及方法[P].中国专利：CN102736531A,2012-10-17.
[23]徐奕昕,白焰,赵天阳,王仁书.泊松分布下无线传感器网络多目标覆盖控制[J].计算机应用,2013,33(07)：1820-1824+1832.
[24]李秋灵,白焰,王仁书.具有容错性的洪泛时间同步算法研究[J].计算机仿真,2013,30(12)：257-260.
[25]李玉凯,白焰,高喜奎,郑源滨,王仁书.能量高效的无线传感器网络可靠转发协议[J].计算机应用,2011,31(01)：202-207.
[26]Yun Ju, Yan Bai, Yaochun Zhu, Renshu Wang, Yukai Li. Integration in the Heterogeneous Wireless Sensor Networks Based on Network Layer [J]. Sensors & Transducers Journal,2013,23(Special Issue):70-74.
[27]Yun Ju,, Yan Bai, Yaochun Zhu, Renshu Wang,Yukai Li. Adaptive Hierarchical Handoff Optimization Scheme for Heterogeneous Wireless Sensor Networks [J]. Sensors & Transducers Journal,2013,23(Special Issue):105-110.
[28]王仁书,白焰,赵坚钧等.无线监测系统在电站顺序控制系统中的应用[J].化工自动化及仪表,2012,39(02)：162-166.
[29]M. Tubaishat, P. Zhuang, Q. Qi, et al. Wireless sensor networks in intelligent transportation system [J]. Wireless Communications and Mobile Computing,2009, 9(3):287-302.
[30]吴迎年,张建华,侯国莲等.网络控制系统研究综述(Ⅰ)[J].现代电力,2003,20(5)：74-79.
[31]吴迎年,张建华,侯国莲等.网络控制系统研究综述(Ⅱ)[J].现代电力,2003, 20(6):54-61.
[32]Hopcroft J E. Introduction to automata theory, languages, and computation [M]. Pearson Addison Wesley,2007.
[33]Hoare C A R. Communicating sequential processes [M]. Englewood Cliffs: Prentice-hall,1985.
[34]Milner R. Calculi for synchrony and asynchrony [J]. Theoretical computer science, 1983,25(3):267-310.
[35]Mazurkiewicz A. Traces, histories, graphs:Instances of a process monoid [M]. Berlin Germany:Springer Berlin Heidelberg,1984.
[36]Grabowski J, Graubmann P, Rudolph E. The standardization of message sequence charts [C]. Software Engineering Standards Symposium,1993. Proceedings.1993. IEEE,1993:48-63.
[37]Cohen G, Dubois D, Quadrat J, et al. A linear-system-theoretic view of discrete-event processes and its use for performance evaluation in manufacturing [J]. Automatic Control, IEEE Transactions on,1985,30(3):210-220.
[38]Jackson J R. Jobshop-like queueing systems [J]. Management science,1963,10(1): 131-142.
[39]Keilson J. Systems of independent Markov components and their transient behavior [J]. Reliability and Fault Tree Analysis,1975:351-364.
[40]Holloway L E, Krogh B H, Giua A. A survey of Petri net methods for controlled discrete event systems [J]. Discrete Event Dynamic Systems,1997,7(2):151-190.
[41]Haenggi M. Mobile sensor-actuator networks:opportunities and challenges[C]. Cellular Neural Networks and Their Applications,2002. (CNNA 2002). Proceedings of the 2002 7th IEEE International Workshop on. IEEE,2002:283-290.
[42]中华人民共和国国务院.国家中长期科学和技术发展规划纲要(2006-2020年),2006.
[43]彭丽萍,岳东.无线网络控制系统的研究[J].控制工程,2006,13(5)：481-484.
[44]韩安太.无线网络控制系统中的延时分析及算法设计[D].杭州：浙江大学,2007.
[45]夏立,江汉红.分布式传感器网络[M].北京：电子工业出版社,2010.
[46]蒋昌俊.离散事件动态系统的PN机理论[M].北京：科学出版社,2000.
[47]Akyildiz, I. F. and I. H. Kasimoglu. Wireless sensor and actor networks:research challenges [J]. Ad Hoc Networks,2004,2(4):351-367.
[48]闫效莺,程国建,周冠武.基于QPSO的WSAN中执行器优化部署研究[J].计算机应用研究,2012,29(10)：3873-3875.
[49]李方敏,徐文君,刘新华等.无线传感器/执行器网络中能量有效的实时分簇路由协议[J].计算机研究与发展,2008,45(1)：26-33.
[50]刘亚雄.基于数据融合的无线传感器执行器网络数据可靠传输[D].上海：上海 交通大学,2012.
[51]易军,石为人,唐云建等.无线传感器/执行器网络任务动态调度策略[J].电子学报,2010,38(6)：1239-1244.
[52]易军,石为人,许磊.无线传感器/执行器网络多目标任务调度策略[J].控制与决策,2011,26(2)：191-195.
[53]曹向辉.无线传感器/执行器网络的体系结构与算法研究[D].杭州：浙江大学,2011.
[54]John K H, Tiegelkamp M. IEC 61131-3:programming industrial automation systems: concepts and programming languages, requirements for programming systems, decision-making aids [M]. Berlin Germany:Springer,2010.
[55]崔坚,赵欣,任术才.西门子S7可编程序控制器——STEP7编程指南[M].北京：机械工业出版社,2009.
[56]王生原,余鹏,霍金键.系统工程Petri网—建模、验证与应用指南[M].北京：电子工业出版社,2005.
[57]魏庆福.现场总线技术的发展与工业以太网综述[J].工业控制计算机,2002,15(01)：1-5.
[58]Tarokh V, Seshadri N, Calderbank A R. Space-time codes for high data rate wireless communication:Performance criterion and code construction [J]. Information Theory, IEEE Transactions on,1998,44(2):744-765.
[59]官晓妍,刘建伟.LDPC码编码方案研究与发展[J].通信技术,2009,41(10)：64-66.
[60]唐智灵,杨小牛,李建东.基于多重判别分析和分形维的数字调制样式自动识别[J].四川大学学报(工程科学版),2012,44(002)：117-121.
[61]Holger Karl, Andreas Willig.无线传感器网络协议与体系结构[M].北京：电子工业出版社,2007.
[62]Wang R, Bai Y, Wang F. The Application of Delay Estimation in Binary Control of Sequence Control in Power Plant Based on ZigBee[C]. Advances in Computer Science, Environment, Ecoinformatics, and Education. Berlin Germany:Springer Berlin Heidelberg,2011:102-106.
[63]L. Kleinrock and F.A.Tobagi. Packet switching in radio channels:Part I carrier sense multiple access models and their throughput/delay characteristic [J]. IEEE Transactions on communications,1975,23(12):1400-1416.
[64]B.A. Harvey and S.B. Wicker. Packet combining systems based on the viterbi decoder [J]. IEEE Transaction on Communications,1994,42(2):1544-1557.
[65]K. Sohrabi, J. Gao, V. Ailawadhi and G.J. Pottie. Protocols for self-organization of a wireless sensor network [J]. IEEE Personal Communications,2000,7(5): 16-27.
[66]Rajendran V, Obraczka K, Garcia-Luna-Aceves J J. Energy-efficient, collision-free medium access control for wireless sensor networks [J]. Wireless Networks,2006, 12(1):63-78.
[67]W. Ye, J. Heidemann, and D. Estrin, An energy-efficient MAC protocol for wireless sensor networks [C]. In 21st Conference of the IEEE Computer and Communications Societies (INFOCOM),2002,3:1567-1576.
[68]Van Dam T, Langendoen K. An adaptive energy-efficient MAC protocol for wireless sensor networks[C]. Proceedings of the 1st international conference on Embedded networked sensor systems. ACM,2003:171-180.
[69]Shuguang Cui, Ritesh Madan,Andrea, J.Goldsmith et al. Cross-Layer Energy and Delay Optimization in Small-Scale Sensor Networks [J]. IEEE Transactions on Wireless Communications,2007,6(10):3688-3689.
[70]Hosam M.F.AboElFotoh, S.S.Iyengar, Krishnendu Chakrabarty. Computing Reliability and Message Delay for Cooperative Wireless Distributed Sensor Networks Subject to Random Failures [J]. IEEE Transactions on Reliability,2005, 54(1):145-155.
[71]Zhang Y, He C, Jiang L. Modeling the S-MAC protocol in single-hop wireless sensor networks [C]. Communications,2008. ICC'08. IEEE International Conference on. IEEE,2008:317-321.
[72]MacKenzie R, O'Farrell T. Throughput and delay analysis for p-persistent CSMA with heterogeneous traffic [J]. Communications, IEEE Transactions on,2010, 58(10):2881-2891.
[73]关守平,孙兰香.长延时网络控制系统的建模与控制[J].控制与决策,2006,21(3)：311-314.
[74]Gao H, Chen T, Lam J. A new delay system approach to network-based control [J]. Automatica,2008,44(1):39-52.
[75]Bai J, Su H, Gao J, et al. Modeling and stabilization of a wireless network control system with packet loss and time delay [J]. Journal of the Franklin Institute,2012, 349(7):2420-2430.
[76]李建宁.无线网络控制系统的建模与控制[D].杭州：浙江大学,2013.
[77]Alam, M. D. Z., Patra, C. C., Patra, C., et al.. Bit Error Rate (BER) Performance Enhancement Technique of a Wireless Fading Channel [C].2009 Isecs International Colloquium on Computing, Communication, Control, and Management, New York, 2009,4:647-650.
[78]Chiu C C, Chen C H, Liao S H, et al. Bit error rate reduction by smart UWB antenna array in indoor wireless communication [J]. Journal of Applied Science and Engineering,2012,15(2):139-148.
[79]Adachi F, Takeda K. Bit error rate analysis of DS-CDMA with joint frequency-domain equalization and antenna diversity combining [J]. IEICE transactions on communications,2004,87(10):2991-3002.
[80]Di Renzo M, Haas H, Grant P M. Spatial modulation for multiple-antenna wireless systems:a survey [J]. Communications Magazine, IEEE,2011,49(12):182-191.
[81]Zummo S A, Yeh P, Stark W E. Bit error probability of bit-interleaved coded modulation (BICM) in wireless environments [C]. IEEE International Symposium on Information Theory,2005,1:739.
[82]Altamirano, C. D., C. de Almeida. Evaluation of the Effects of Co-Channel Interference on the Bit Error Rate of Wireless Networks with Error Correcting Codes in Fading Channels [J]. Ieee Latin America Transactions,2013,11(3):892-895.
[83]Chen, C. and A. Abdi. Bit error rate in multipath wireless channels with several specular paths [J]. Electronics Letters,2011,47(18):1046-U1588.
[84]Ilyas M. U., Radha H.. A channel model for the bit error rate process in 802.15.4 LR-WPAN wireless channels [C].2008 Ieee International Conference on Communications, Proceedings, New York,2008,1-13:257-261.
[85]T.S. Rappaport. Wireless Communications-Principles and Practice [M]. NJ: Prentice Hall, Upper Saddle River,2002.
[86]Erdal Cayirci, Chunming Rong. Security in Wireless Ad Hoc and Sensor Network [M]. USA New Jersey:John Wiley & Sons,2009.
[87]姚予疆,申萍.数字通信测量仪器[M].北京：人民邮电出版社,2007.
[88]Waltenegus Dargie, Christian Poellabauer. Fundamentals of Wireless Sensor Networks:Theory and Practice [M]. USA New Jersey:John Wiley & Sons,2010.
[89]Bernard Sklar. Digital Communication-Fundamentals and Applications (2nd) [M]. Beijing:Publishing House of Electronics Industry,2002.
[90]徐平平,宋铁成,叶芝慧等.数字通信——基础与应用(2nd)[M].北京：电子工业出版社,2002.
[91]Wang R S, Bai Y, Xu Y X, et al. The Analysis of Wireless Channel in the Workshop of Chemical Water Treatment in Power Plant [J]. Advanced Materials Research, 2012,424:728-731.
[92]王维平.离散事件系统建模与仿真(第2版)[M].北京：科学出版社,2007.
[93]郑大钟,赵千川.离散事件动态系统[M].北京：清华大学出版社,2000.
[94]林闯.随机Petri网和系统性能评价[M].清华大学出版社,2005.
[95]Shuaib A. H., Mahmoodi T, Aghvami A. H. A Timed Petri Net Model for the IEEE 802.15.4 CSMA-CA Process [C]. IEEE 20th International symposium on personal, indoor and mobile radio communications,2009:1204-1210.
[96]Shimura, T., J. Lobo, et al. An extended Petri net model for normal logic programs [J]. Knowledge and Data Engineering, IEEE Transactions on,1995,7(1):150-162.
[97]Jensen K. Coloured Petri nets and the invariant-method [J]. Theoretical computer science,1981,14(3):317-336.
[98]Lin C, Marinescu D C. Stochastic high-level Petri nets and applications [M]//High-level Petri Nets. Berlin Germany:Springer Berlin Heidelberg,1991: 459-469.
[99]Marsan M.A., Chiola G. On petri nets with deterministic and exponentially distributed firing times[C]. Lecture Notes on Computer Science,1987,266:132-145.
[100]张耀鸿,樊建才,廖晓林.基于Petri网的指挥控制流程仿真方法[J].系统仿真学报,2012,24(7)：1418-1421.
[101]原菊梅,侯朝桢,王小艺等.考虑环境因素的分布式系统可靠性建模及其分析[J].控制与决策,2007,22(3)：309-312+317.
[102]Yen H C. Concurrency, Synchronization, and Conflicts in Petri nets [C]. Proceedings of the 13th international conference on Implementation and Applications of Automata, San Francisco, United states. Berlin Germany: Springer-Verlag,2008:33-35.
[103]Gutierrez J. Logics and Bisimulation. Games for Concurrency, Causality and Conflict [C]. Proc. Foundations of Software Science and Computational Structures, York, UK. Berlin Germany:Springer,2009:48-62.
[104]Wightkin, N.Buy, U. Darabi, H.. Formal Modeling of Sequential Function Charts With Time Petri Nets [J]. IEEE Transactions on Control Systems Technology (S1063-6536),2011,19(2):455-464.
[105]Hellgren, A.Fabian, M.Lennartson, B. On the Execution of Sequential Function Charts [J]. Control Engineering Practice (S0967-0661),2005,13(10):1283-1293.
[106]袁崇义.Petri网原理[M].北京：电子工业出版社,1998.
[107]Zhong D, Qi Z. A petri net based approach for reliability prediction of web services[C]//On the Move to Meaningful Internet Systems 2006:OTM 2006 Workshops. Springer Berlin Heidelberg,2006:116-125.
[108]Volovoi V, Kavalieratos G, Waters M, et al. Modeling the reliability of distribution systems using Petri nets[C]. Harmonics and Quality of Power,2004.11th International Conference on. IEEE,2004:567-572.
[109]R. David, H. Alia. Discrete, Continuous and Hybrid Petri Nets [M]. Berlin Germany:Springer,2005.
[110]马万治.无线通信抗干扰技术性能研究[D].成都：电子科技大学,2012.
[111]J G. Proakis. Digital Communications [M]. New York, USA:McGraw-Hill,2009.
[112]Renshu Wang, Yan Bai, Yixin Xu, et al. The Analysis of Wireless Channel in the Workshop of Chemical Water Treatment in Power Plant [C].2012 2nd International Conference on Engineering Materials, Energy, Management and Control, Wuhan, China. Switzerland:Trans Tech Publications,2012:728-31.
[113]王岩,孙增圻.网络控制系统分析与设计[M].北京：清华大学出版社,2009.
[114]Cheng D. Semi-tensor product of matrices and its application to Morgen's problem [J]. Science in China Series:Information Sciences,2001,44(3):195-212.
[115]Jacob F, Monod J. Genetic regulatory mechanisms in the synthesis of proteins [J]. Journal of molecular biology,1961,3(3):318-356.
[116]Kauffman S A. Metabolic stability and epigenesis in randomly constructed genetic nets [J]. Journal of theoretical biology,1969,22(3):437-467.
[117]Shmulevich I, Dougherty E R, Kim S, et al. Probabilistic Boolean networks:a rule-based uncertainty model for gene regulatory networks [J]. Bioinformatics, 2002,18(2):261-274.
[118]Silvescu A, Honavar V. Temporal boolean network models of genetic networks and their inference from gene expression time series [J]. Complex Systems,2001,13(1): 61-78.
[119]Brun M, Dougherty E R, Shmulevich I. Steady-state probabilities for attractors in probabilistic Boolean networks [J]. Signal Processing,2005,85(10):1993-2013.
[120]Klemm K, Bornholdt S. Stable and unstable attractors in Boolean networks [J]. Physical Review E,2005,72(5):055101.
[121]Pal R, Datta A, Bittner M L, et al. Intervention in context-sensitive probabilistic Boolean networks [J]. Bioinformatics,2005,21(7):1211-1218.
[122]Serra R, Villani M, Semeria A. Genetic network models and statistical properties of gene expression data in knock-out experiments [J]. Journal of theoretical biology, 2004,227(1):149-157.
[123]Faure A, Naldi A, Chaouiya C, et al. Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle [J]. Bioinformatics,2006,22(14): e124-e131.
[124]Bornholdt S. Boolean network models of cellular regulation:prospects and limitations [J]. Journal of the Royal Society Interface,2008,5(Suppl 1):S85-S94.
[125]Akutsu T, Hayashida M, Ching W K, et al. Control of Boolean networks:hardness results and algorithms for tree structured networks [J]. Journal of Theoretical Biology,2007,244(4):670-679.
[126]Liu Q. An optimal control approach to probabilistic Boolean networks [J]. Physica A:Statistical Mechanics and its Applications,2012,391(24):6682-6689.
[127]Kobayashi K, Hiraishi K. Optimal control of Boolean biological networks modeled by Petri nets [J]. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences,2013,96(2):532-539.
[128]Kobayashi K, Hiraishi K. Optimal control of probabilistic Boolean networks using polynomial optimization [J]. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences,2012,95(9):1512-1517.
[129]Cheng, D. Z., H. S. Qi. Controllability and observability of Boolean control networks [J]. Automatica,2009,45(7):1659-1667.
[130]Chen H, Sun J. A new approach for global controllability of higher order Boolean control network [J]. Neural Networks,2013,39:12-17.
[131]Li R, Yang M, Chu T. State feedback stabilization for Boolean control networks [J]. Automatic Control, IEEE Transactions on,2013,58(7):1853-1857.
[132]Li H, Wang Y. On reachability and controllability of switched Boolean control networks [J]. Automatica,2012,48(11):2917-2922.
[133]Li F, Sun J. Controllability of Boolean control networks with time delays in states [J]. Automatica,2011,47(3):603-607.
[134]Li F, Sun J. Observability of Boolean control networks with state time delays [J]. Neural Networks, IEEE Transactions on,2011,22(6):948-954.
[135]Zhao Y, Qi H, Cheng D. Input-state incidence matrix of Boolean control networks and its applications [J]. Systems & Control Letters,2010,59(12):767-774.
[136]Lijun Zhang, Kuize Zhang. Controllability and Observability of Boolean Control Networks With Time-Variant Delays in States [J]. Neural Networks and Learning Systems, IEEE Transactions on.2013,24(9):1478-1484.
[137]Li, Fangfei,Sun, Jitao. Controllability and optimal control of a temporal Boolean network [J]. Neural Networks,2012, (34):10-17.
[138]Zhang, L., Feng, J., Yao, J. Controllability and observability of switched Boolean control networks [J]. IET Control Theory and Applications.2012,6(16): 2477-2484.
[139]程代展,齐洪胜.矩阵的半张量积—理论与应用(第2版)[M].北京：科学出版社,2007.
[140]Cheng D, Qi H. A linear representation of dynamics of Boolean networks [J]. Automatic Control, IEEE Transactions on,2010,55(10):2251-2258.
[141]Cheng, D. Z., Li, Z. Q., Qi, H. S. Realization of Boolean control networks [J]. Automatica,2010,46(1):62-69.
[142]Zhao Y, Cheng D. Controllability and stabilizability of probabilistic logical control networks[C]. Decision and Control (CDC),2012 IEEE 51st Annual Conference on. IEEE,2012:6729-6734.
[143]Zhang, L. and K. Zhang. Controllability and Observability of Boolean Control Networks With Time-Van ant Delays in States [J]. Neural Networks and Learning Systems, IEEE Transactions on,2013,24(9):1478-1484.
[144]范国伟,王平,王伟等.组态技术入门与应用实例编著[M].北京：中国电力出版社,2012.
[145]彭瑜,何衍庆.IEC 61131-3编程语言及应用基础[M].北京：机械工业出版社,2009.
[146]崔坚,赵欣,任术才.西门子S7-higraph可编程序控制器——STEP 7编程指南[M].北京：机械工业出版社,2010.
[147]P.Levis, S.Madden, J.Polastre R.Szewczyk, et al. TinyOS:an operating system for sensor networks [M]. Berlin Germany:Ambient Intelligence Springer Berlin Heidelberg,2005.
[148]苏铅坤.无线传感器网络文件系统与重编程技术研究[M].西安：电子科技大学,2010.
[149]Wheeler A. Commercial applications of wireless sensor networks using ZigBee [J]. Communications Magazine, IEEE,2007,45(4):70-77.
[150]瞿雷,刘盛德,胡咸斌.ZigBee2006技术及应用[M].北京：北京航空航天大学出版社,2007.
[151]Huang Y K, Pang A C, Hung H N. An adaptive GTS allocation scheme for IEEE 802.15.4 [J]. Parallel and Distributed Systems, IEEE Transactions on,2008,19(5): 641-651.
[152]Kumarage, H., Khalil, I., Tari, Z., et al. Distributed anomaly detection for industrial wireless sensor networks based on fuzzy data modeling [J]. Journal of Parallel and Distributed Computing,2013,73(6):790-806.
[153]Sukumar G.. Distributed Systems:An Algorithmic Approach [M]. Taylor & Francis Group. University of Iowa City, U.S.A,2007:219.
[154]李玉凯.无线传感器网络高能效可靠数据传输理论及应用研究[D].北京：华北电力大学,2011.
[155]汪凤珠,白焰,王仁书.电厂超滤系统低功耗无线监测网络的设计[J].自动化仪表,2012,33(08)：74-77+80.
[156]李玉凯,白焰,高喜奎.智能分析仪表PROFIBUS-DP接口的研发[J].化工自动化及仪表,2011,38(01)：56-59+64.
[157]叶园,白焰,王仁书.InTouch在无线超滤监控系统中的应用[J].化工自动化及仪表,2012,39(02)：228-231+240.
[158]Heo J., Hong J., Cho Y.. EARQ:Energy Aware Routing for Real-Time and Reliable Communication in Wireless Industrial Sensor Networks [J]. IEEE Transactions on Industrial Informatics,2008,5(1):3-11.
[159]中国电子信息产业发展研究院.2011中国物联网产业发展指南[M].北京：机械工业出版社,2011.
[160]Cavalcanti D, Agrawal D, Cordeiro C, et al. Issues in integrating cellular networks WLANs, AND MANETs:a futuristic heterogeneous wireless network [J]. Wireless Communications, IEEE,2005,12(3):30-41.
[2]陈慧琴,蔡均.工业控制系统信息化发展综述[J].仪器仪表用户,2007,(14)1：1-2.
[3]张桢,牛玉刚.DCS与现场总线综述[J].电气自动化,2013,35(1)：4-6+46.
[4]Gungor V C, Hancke G P. Industrial wireless sensor networks:Challenges, design principles, and technical approaches [J]. Industrial Electronics, IEEE Transactions on, 2009,56(10):4258-4265.
[5]Low K S, Win W N N, Er M J. Wireless sensor networks for industrial environments [C]. Computational Intelligence for Modelling, Control and Automation,2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on. IEEE,2005,2:271-276.
[6]Andreas W. Recent and Emerging Topics in Wireless Industrial Communications:A Selection [J]. IEEE Transactions on Industrial Informatics,2008,4(2):102-124.
[7]白焰,吴鸿,杨国田.分散控制系统与现场总线控制系统——基础、评选、设计和应用[M].北京：中国电力出版社,2001.
[8]吕俊.分布式控制系统中的通信机制的研究[D].杭州：浙江大学,2003.
[9]刘向杰,彭一民.现场总线控制系统的现状与发展[J].电网技术,1999,23(3)：47-50.
[10]曹霖.分布式控制系统的设计与实现[D].南京：南京航空航天大学,2011.
[11]潘凤萍,陈世和,张红福等.1000MW超超临界机组自启停控制系统总体方案设计与应用[J].中国电力,2009,42(10)：15-18.
[12]王志祥,黄伟.热工保护与顺序控制[M].北京：中国电力出版社,2008.
[13]施玉晨.无线中继系统中的编码与协作传输技术研究[D].西安：西安电子科技大学,2012.
[14]王亚刚,许晓鸣,彭瑜等.无线传感器网络阀门检漏仪表的设计[J].自动化仪表,2010,31(4)：22-24.
[15]湛浩晏,孙长嵩,吴珊等.ZigBee技术在煤矿井下救援系统中的应用[J].计算机工程与应用,2006,42(24)：181-183.
[16]Song J, Han S, Mok A K, et al. WirelessHART:Applying wireless technology in real-time industrial process control [C]. Real-Time and Embedded Technology and Applications Symposium,2008. RTAS'08. IEEE. IEEE,2008:377-386.
[17]王平,刘其琛,王恒等.一种适用于ISA100.11a工业无线网络的通信调度方法[J].仪器仪表学报,2011,32(5)：1189-1195.
[18]刘扬,曾鹏,尚志军等.基于工业无线网络WIA技术的储油罐监测系统[J].仪器仪表标准化与计量,2009,05：20-21+24.
[19]曾鹏,王军.基于WIA技术的油井远程计量与优化控制系统[J].自动化博览,2010,02：18-20+30.
[20]王仁书,白焰,汪凤珠等.无线监控系统在电站化学水处理超滤系统中的应用[J].中国电力,2012,45(07)：84-88.
[21]王仁书,白焰,李秋灵等。基于无线传输顺控系统的超滤系统性能分析与仿真[J].系统仿真学报,2014,26(1)：23-28.
[22]白焰,王仁书,汪凤珠等.一种基于无线网络的分布式自学习顺序控制系统及方法[P].中国专利：CN102736531A,2012-10-17.
[23]徐奕昕,白焰,赵天阳,王仁书.泊松分布下无线传感器网络多目标覆盖控制[J].计算机应用,2013,33(07)：1820-1824+1832.
[24]李秋灵,白焰,王仁书.具有容错性的洪泛时间同步算法研究[J].计算机仿真,2013,30(12)：257-260.
[25]李玉凯,白焰,高喜奎,郑源滨,王仁书.能量高效的无线传感器网络可靠转发协议[J].计算机应用,2011,31(01)：202-207.
[26]Yun Ju, Yan Bai, Yaochun Zhu, Renshu Wang, Yukai Li. Integration in the Heterogeneous Wireless Sensor Networks Based on Network Layer [J]. Sensors & Transducers Journal,2013,23(Special Issue):70-74.
[27]Yun Ju,, Yan Bai, Yaochun Zhu, Renshu Wang,Yukai Li. Adaptive Hierarchical Handoff Optimization Scheme for Heterogeneous Wireless Sensor Networks [J]. Sensors & Transducers Journal,2013,23(Special Issue):105-110.
[28]王仁书,白焰,赵坚钧等.无线监测系统在电站顺序控制系统中的应用[J].化工自动化及仪表,2012,39(02)：162-166.
[29]M. Tubaishat, P. Zhuang, Q. Qi, et al. Wireless sensor networks in intelligent transportation system [J]. Wireless Communications and Mobile Computing,2009, 9(3):287-302.
[30]吴迎年,张建华,侯国莲等.网络控制系统研究综述(Ⅰ)[J].现代电力,2003,20(5)：74-79.
[31]吴迎年,张建华,侯国莲等.网络控制系统研究综述(Ⅱ)[J].现代电力,2003, 20(6):54-61.
[32]Hopcroft J E. Introduction to automata theory, languages, and computation [M]. Pearson Addison Wesley,2007.
[33]Hoare C A R. Communicating sequential processes [M]. Englewood Cliffs: Prentice-hall,1985.
[34]Milner R. Calculi for synchrony and asynchrony [J]. Theoretical computer science, 1983,25(3):267-310.
[35]Mazurkiewicz A. Traces, histories, graphs:Instances of a process monoid [M]. Berlin Germany:Springer Berlin Heidelberg,1984.
[36]Grabowski J, Graubmann P, Rudolph E. The standardization of message sequence charts [C]. Software Engineering Standards Symposium,1993. Proceedings.1993. IEEE,1993:48-63.
[37]Cohen G, Dubois D, Quadrat J, et al. A linear-system-theoretic view of discrete-event processes and its use for performance evaluation in manufacturing [J]. Automatic Control, IEEE Transactions on,1985,30(3):210-220.
[38]Jackson J R. Jobshop-like queueing systems [J]. Management science,1963,10(1): 131-142.
[39]Keilson J. Systems of independent Markov components and their transient behavior [J]. Reliability and Fault Tree Analysis,1975:351-364.
[40]Holloway L E, Krogh B H, Giua A. A survey of Petri net methods for controlled discrete event systems [J]. Discrete Event Dynamic Systems,1997,7(2):151-190.
[41]Haenggi M. Mobile sensor-actuator networks:opportunities and challenges[C]. Cellular Neural Networks and Their Applications,2002. (CNNA 2002). Proceedings of the 2002 7th IEEE International Workshop on. IEEE,2002:283-290.
[42]中华人民共和国国务院.国家中长期科学和技术发展规划纲要(2006-2020年),2006.
[43]彭丽萍,岳东.无线网络控制系统的研究[J].控制工程,2006,13(5)：481-484.
[44]韩安太.无线网络控制系统中的延时分析及算法设计[D].杭州：浙江大学,2007.
[45]夏立,江汉红.分布式传感器网络[M].北京：电子工业出版社,2010.
[46]蒋昌俊.离散事件动态系统的PN机理论[M].北京：科学出版社,2000.
[47]Akyildiz, I. F. and I. H. Kasimoglu. Wireless sensor and actor networks:research challenges [J]. Ad Hoc Networks,2004,2(4):351-367.
[48]闫效莺,程国建,周冠武.基于QPSO的WSAN中执行器优化部署研究[J].计算机应用研究,2012,29(10)：3873-3875.
[49]李方敏,徐文君,刘新华等.无线传感器/执行器网络中能量有效的实时分簇路由协议[J].计算机研究与发展,2008,45(1)：26-33.
[50]刘亚雄.基于数据融合的无线传感器执行器网络数据可靠传输[D].上海：上海 交通大学,2012.
[51]易军,石为人,唐云建等.无线传感器/执行器网络任务动态调度策略[J].电子学报,2010,38(6)：1239-1244.
[52]易军,石为人,许磊.无线传感器/执行器网络多目标任务调度策略[J].控制与决策,2011,26(2)：191-195.
[53]曹向辉.无线传感器/执行器网络的体系结构与算法研究[D].杭州：浙江大学,2011.
[54]John K H, Tiegelkamp M. IEC 61131-3:programming industrial automation systems: concepts and programming languages, requirements for programming systems, decision-making aids [M]. Berlin Germany:Springer,2010.
[55]崔坚,赵欣,任术才.西门子S7可编程序控制器——STEP7编程指南[M].北京：机械工业出版社,2009.
[56]王生原,余鹏,霍金键.系统工程Petri网—建模、验证与应用指南[M].北京：电子工业出版社,2005.
[57]魏庆福.现场总线技术的发展与工业以太网综述[J].工业控制计算机,2002,15(01)：1-5.
[58]Tarokh V, Seshadri N, Calderbank A R. Space-time codes for high data rate wireless communication:Performance criterion and code construction [J]. Information Theory, IEEE Transactions on,1998,44(2):744-765.
[59]官晓妍,刘建伟.LDPC码编码方案研究与发展[J].通信技术,2009,41(10)：64-66.
[60]唐智灵,杨小牛,李建东.基于多重判别分析和分形维的数字调制样式自动识别[J].四川大学学报(工程科学版),2012,44(002)：117-121.
[61]Holger Karl, Andreas Willig.无线传感器网络协议与体系结构[M].北京：电子工业出版社,2007.
[62]Wang R, Bai Y, Wang F. The Application of Delay Estimation in Binary Control of Sequence Control in Power Plant Based on ZigBee[C]. Advances in Computer Science, Environment, Ecoinformatics, and Education. Berlin Germany:Springer Berlin Heidelberg,2011:102-106.
[63]L. Kleinrock and F.A.Tobagi. Packet switching in radio channels:Part I carrier sense multiple access models and their throughput/delay characteristic [J]. IEEE Transactions on communications,1975,23(12):1400-1416.
[64]B.A. Harvey and S.B. Wicker. Packet combining systems based on the viterbi decoder [J]. IEEE Transaction on Communications,1994,42(2):1544-1557.
[65]K. Sohrabi, J. Gao, V. Ailawadhi and G.J. Pottie. Protocols for self-organization of a wireless sensor network [J]. IEEE Personal Communications,2000,7(5): 16-27.
[66]Rajendran V, Obraczka K, Garcia-Luna-Aceves J J. Energy-efficient, collision-free medium access control for wireless sensor networks [J]. Wireless Networks,2006, 12(1):63-78.
[67]W. Ye, J. Heidemann, and D. Estrin, An energy-efficient MAC protocol for wireless sensor networks [C]. In 21st Conference of the IEEE Computer and Communications Societies (INFOCOM),2002,3:1567-1576.
[68]Van Dam T, Langendoen K. An adaptive energy-efficient MAC protocol for wireless sensor networks[C]. Proceedings of the 1st international conference on Embedded networked sensor systems. ACM,2003:171-180.
[69]Shuguang Cui, Ritesh Madan,Andrea, J.Goldsmith et al. Cross-Layer Energy and Delay Optimization in Small-Scale Sensor Networks [J]. IEEE Transactions on Wireless Communications,2007,6(10):3688-3689.
[70]Hosam M.F.AboElFotoh, S.S.Iyengar, Krishnendu Chakrabarty. Computing Reliability and Message Delay for Cooperative Wireless Distributed Sensor Networks Subject to Random Failures [J]. IEEE Transactions on Reliability,2005, 54(1):145-155.
[71]Zhang Y, He C, Jiang L. Modeling the S-MAC protocol in single-hop wireless sensor networks [C]. Communications,2008. ICC'08. IEEE International Conference on. IEEE,2008:317-321.
[72]MacKenzie R, O'Farrell T. Throughput and delay analysis for p-persistent CSMA with heterogeneous traffic [J]. Communications, IEEE Transactions on,2010, 58(10):2881-2891.
[73]关守平,孙兰香.长延时网络控制系统的建模与控制[J].控制与决策,2006,21(3)：311-314.
[74]Gao H, Chen T, Lam J. A new delay system approach to network-based control [J]. Automatica,2008,44(1):39-52.
[75]Bai J, Su H, Gao J, et al. Modeling and stabilization of a wireless network control system with packet loss and time delay [J]. Journal of the Franklin Institute,2012, 349(7):2420-2430.
[76]李建宁.无线网络控制系统的建模与控制[D].杭州：浙江大学,2013.
[77]Alam, M. D. Z., Patra, C. C., Patra, C., et al.. Bit Error Rate (BER) Performance Enhancement Technique of a Wireless Fading Channel [C].2009 Isecs International Colloquium on Computing, Communication, Control, and Management, New York, 2009,4:647-650.
[78]Chiu C C, Chen C H, Liao S H, et al. Bit error rate reduction by smart UWB antenna array in indoor wireless communication [J]. Journal of Applied Science and Engineering,2012,15(2):139-148.
[79]Adachi F, Takeda K. Bit error rate analysis of DS-CDMA with joint frequency-domain equalization and antenna diversity combining [J]. IEICE transactions on communications,2004,87(10):2991-3002.
[80]Di Renzo M, Haas H, Grant P M. Spatial modulation for multiple-antenna wireless systems:a survey [J]. Communications Magazine, IEEE,2011,49(12):182-191.
[81]Zummo S A, Yeh P, Stark W E. Bit error probability of bit-interleaved coded modulation (BICM) in wireless environments [C]. IEEE International Symposium on Information Theory,2005,1:739.
[82]Altamirano, C. D., C. de Almeida. Evaluation of the Effects of Co-Channel Interference on the Bit Error Rate of Wireless Networks with Error Correcting Codes in Fading Channels [J]. Ieee Latin America Transactions,2013,11(3):892-895.
[83]Chen, C. and A. Abdi. Bit error rate in multipath wireless channels with several specular paths [J]. Electronics Letters,2011,47(18):1046-U1588.
[84]Ilyas M. U., Radha H.. A channel model for the bit error rate process in 802.15.4 LR-WPAN wireless channels [C].2008 Ieee International Conference on Communications, Proceedings, New York,2008,1-13:257-261.
[85]T.S. Rappaport. Wireless Communications-Principles and Practice [M]. NJ: Prentice Hall, Upper Saddle River,2002.
[86]Erdal Cayirci, Chunming Rong. Security in Wireless Ad Hoc and Sensor Network [M]. USA New Jersey:John Wiley & Sons,2009.
[87]姚予疆,申萍.数字通信测量仪器[M].北京：人民邮电出版社,2007.
[88]Waltenegus Dargie, Christian Poellabauer. Fundamentals of Wireless Sensor Networks:Theory and Practice [M]. USA New Jersey:John Wiley & Sons,2010.
[89]Bernard Sklar. Digital Communication-Fundamentals and Applications (2nd) [M]. Beijing:Publishing House of Electronics Industry,2002.
[90]徐平平,宋铁成,叶芝慧等.数字通信——基础与应用(2nd)[M].北京：电子工业出版社,2002.
[91]Wang R S, Bai Y, Xu Y X, et al. The Analysis of Wireless Channel in the Workshop of Chemical Water Treatment in Power Plant [J]. Advanced Materials Research, 2012,424:728-731.
[92]王维平.离散事件系统建模与仿真(第2版)[M].北京：科学出版社,2007.
[93]郑大钟,赵千川.离散事件动态系统[M].北京：清华大学出版社,2000.
[94]林闯.随机Petri网和系统性能评价[M].清华大学出版社,2005.
[95]Shuaib A. H., Mahmoodi T, Aghvami A. H. A Timed Petri Net Model for the IEEE 802.15.4 CSMA-CA Process [C]. IEEE 20th International symposium on personal, indoor and mobile radio communications,2009:1204-1210.
[96]Shimura, T., J. Lobo, et al. An extended Petri net model for normal logic programs [J]. Knowledge and Data Engineering, IEEE Transactions on,1995,7(1):150-162.
[97]Jensen K. Coloured Petri nets and the invariant-method [J]. Theoretical computer science,1981,14(3):317-336.
[98]Lin C, Marinescu D C. Stochastic high-level Petri nets and applications [M]//High-level Petri Nets. Berlin Germany:Springer Berlin Heidelberg,1991: 459-469.
[99]Marsan M.A., Chiola G. On petri nets with deterministic and exponentially distributed firing times[C]. Lecture Notes on Computer Science,1987,266:132-145.
[100]张耀鸿,樊建才,廖晓林.基于Petri网的指挥控制流程仿真方法[J].系统仿真学报,2012,24(7)：1418-1421.
[101]原菊梅,侯朝桢,王小艺等.考虑环境因素的分布式系统可靠性建模及其分析[J].控制与决策,2007,22(3)：309-312+317.
[102]Yen H C. Concurrency, Synchronization, and Conflicts in Petri nets [C]. Proceedings of the 13th international conference on Implementation and Applications of Automata, San Francisco, United states. Berlin Germany: Springer-Verlag,2008:33-35.
[103]Gutierrez J. Logics and Bisimulation. Games for Concurrency, Causality and Conflict [C]. Proc. Foundations of Software Science and Computational Structures, York, UK. Berlin Germany:Springer,2009:48-62.
[104]Wightkin, N.Buy, U. Darabi, H.. Formal Modeling of Sequential Function Charts With Time Petri Nets [J]. IEEE Transactions on Control Systems Technology (S1063-6536),2011,19(2):455-464.
[105]Hellgren, A.Fabian, M.Lennartson, B. On the Execution of Sequential Function Charts [J]. Control Engineering Practice (S0967-0661),2005,13(10):1283-1293.
[106]袁崇义.Petri网原理[M].北京：电子工业出版社,1998.
[107]Zhong D, Qi Z. A petri net based approach for reliability prediction of web services[C]//On the Move to Meaningful Internet Systems 2006:OTM 2006 Workshops. Springer Berlin Heidelberg,2006:116-125.
[108]Volovoi V, Kavalieratos G, Waters M, et al. Modeling the reliability of distribution systems using Petri nets[C]. Harmonics and Quality of Power,2004.11th International Conference on. IEEE,2004:567-572.
[109]R. David, H. Alia. Discrete, Continuous and Hybrid Petri Nets [M]. Berlin Germany:Springer,2005.
[110]马万治.无线通信抗干扰技术性能研究[D].成都：电子科技大学,2012.
[111]J G. Proakis. Digital Communications [M]. New York, USA:McGraw-Hill,2009.
[112]Renshu Wang, Yan Bai, Yixin Xu, et al. The Analysis of Wireless Channel in the Workshop of Chemical Water Treatment in Power Plant [C].2012 2nd International Conference on Engineering Materials, Energy, Management and Control, Wuhan, China. Switzerland:Trans Tech Publications,2012:728-31.
[113]王岩,孙增圻.网络控制系统分析与设计[M].北京：清华大学出版社,2009.
[114]Cheng D. Semi-tensor product of matrices and its application to Morgen's problem [J]. Science in China Series:Information Sciences,2001,44(3):195-212.
[115]Jacob F, Monod J. Genetic regulatory mechanisms in the synthesis of proteins [J]. Journal of molecular biology,1961,3(3):318-356.
[116]Kauffman S A. Metabolic stability and epigenesis in randomly constructed genetic nets [J]. Journal of theoretical biology,1969,22(3):437-467.
[117]Shmulevich I, Dougherty E R, Kim S, et al. Probabilistic Boolean networks:a rule-based uncertainty model for gene regulatory networks [J]. Bioinformatics, 2002,18(2):261-274.
[118]Silvescu A, Honavar V. Temporal boolean network models of genetic networks and their inference from gene expression time series [J]. Complex Systems,2001,13(1): 61-78.
[119]Brun M, Dougherty E R, Shmulevich I. Steady-state probabilities for attractors in probabilistic Boolean networks [J]. Signal Processing,2005,85(10):1993-2013.
[120]Klemm K, Bornholdt S. Stable and unstable attractors in Boolean networks [J]. Physical Review E,2005,72(5):055101.
[121]Pal R, Datta A, Bittner M L, et al. Intervention in context-sensitive probabilistic Boolean networks [J]. Bioinformatics,2005,21(7):1211-1218.
[122]Serra R, Villani M, Semeria A. Genetic network models and statistical properties of gene expression data in knock-out experiments [J]. Journal of theoretical biology, 2004,227(1):149-157.
[123]Faure A, Naldi A, Chaouiya C, et al. Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle [J]. Bioinformatics,2006,22(14): e124-e131.
[124]Bornholdt S. Boolean network models of cellular regulation:prospects and limitations [J]. Journal of the Royal Society Interface,2008,5(Suppl 1):S85-S94.
[125]Akutsu T, Hayashida M, Ching W K, et al. Control of Boolean networks:hardness results and algorithms for tree structured networks [J]. Journal of Theoretical Biology,2007,244(4):670-679.
[126]Liu Q. An optimal control approach to probabilistic Boolean networks [J]. Physica A:Statistical Mechanics and its Applications,2012,391(24):6682-6689.
[127]Kobayashi K, Hiraishi K. Optimal control of Boolean biological networks modeled by Petri nets [J]. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences,2013,96(2):532-539.
[128]Kobayashi K, Hiraishi K. Optimal control of probabilistic Boolean networks using polynomial optimization [J]. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences,2012,95(9):1512-1517.
[129]Cheng, D. Z., H. S. Qi. Controllability and observability of Boolean control networks [J]. Automatica,2009,45(7):1659-1667.
[130]Chen H, Sun J. A new approach for global controllability of higher order Boolean control network [J]. Neural Networks,2013,39:12-17.
[131]Li R, Yang M, Chu T. State feedback stabilization for Boolean control networks [J]. Automatic Control, IEEE Transactions on,2013,58(7):1853-1857.
[132]Li H, Wang Y. On reachability and controllability of switched Boolean control networks [J]. Automatica,2012,48(11):2917-2922.
[133]Li F, Sun J. Controllability of Boolean control networks with time delays in states [J]. Automatica,2011,47(3):603-607.
[134]Li F, Sun J. Observability of Boolean control networks with state time delays [J]. Neural Networks, IEEE Transactions on,2011,22(6):948-954.
[135]Zhao Y, Qi H, Cheng D. Input-state incidence matrix of Boolean control networks and its applications [J]. Systems & Control Letters,2010,59(12):767-774.
[136]Lijun Zhang, Kuize Zhang. Controllability and Observability of Boolean Control Networks With Time-Variant Delays in States [J]. Neural Networks and Learning Systems, IEEE Transactions on.2013,24(9):1478-1484.
[137]Li, Fangfei,Sun, Jitao. Controllability and optimal control of a temporal Boolean network [J]. Neural Networks,2012, (34):10-17.
[138]Zhang, L., Feng, J., Yao, J. Controllability and observability of switched Boolean control networks [J]. IET Control Theory and Applications.2012,6(16): 2477-2484.
[139]程代展,齐洪胜.矩阵的半张量积—理论与应用(第2版)[M].北京：科学出版社,2007.
[140]Cheng D, Qi H. A linear representation of dynamics of Boolean networks [J]. Automatic Control, IEEE Transactions on,2010,55(10):2251-2258.
[141]Cheng, D. Z., Li, Z. Q., Qi, H. S. Realization of Boolean control networks [J]. Automatica,2010,46(1):62-69.
[142]Zhao Y, Cheng D. Controllability and stabilizability of probabilistic logical control networks[C]. Decision and Control (CDC),2012 IEEE 51st Annual Conference on. IEEE,2012:6729-6734.
[143]Zhang, L. and K. Zhang. Controllability and Observability of Boolean Control Networks With Time-Van ant Delays in States [J]. Neural Networks and Learning Systems, IEEE Transactions on,2013,24(9):1478-1484.
[144]范国伟,王平,王伟等.组态技术入门与应用实例编著[M].北京：中国电力出版社,2012.
[145]彭瑜,何衍庆.IEC 61131-3编程语言及应用基础[M].北京：机械工业出版社,2009.
[146]崔坚,赵欣,任术才.西门子S7-higraph可编程序控制器——STEP 7编程指南[M].北京：机械工业出版社,2010.
[147]P.Levis, S.Madden, J.Polastre R.Szewczyk, et al. TinyOS:an operating system for sensor networks [M]. Berlin Germany:Ambient Intelligence Springer Berlin Heidelberg,2005.
[148]苏铅坤.无线传感器网络文件系统与重编程技术研究[M].西安：电子科技大学,2010.
[149]Wheeler A. Commercial applications of wireless sensor networks using ZigBee [J]. Communications Magazine, IEEE,2007,45(4):70-77.
[150]瞿雷,刘盛德,胡咸斌.ZigBee2006技术及应用[M].北京：北京航空航天大学出版社,2007.
[151]Huang Y K, Pang A C, Hung H N. An adaptive GTS allocation scheme for IEEE 802.15.4 [J]. Parallel and Distributed Systems, IEEE Transactions on,2008,19(5): 641-651.
[152]Kumarage, H., Khalil, I., Tari, Z., et al. Distributed anomaly detection for industrial wireless sensor networks based on fuzzy data modeling [J]. Journal of Parallel and Distributed Computing,2013,73(6):790-806.
[153]Sukumar G.. Distributed Systems:An Algorithmic Approach [M]. Taylor & Francis Group. University of Iowa City, U.S.A,2007:219.
[154]李玉凯.无线传感器网络高能效可靠数据传输理论及应用研究[D].北京：华北电力大学,2011.
[155]汪凤珠,白焰,王仁书.电厂超滤系统低功耗无线监测网络的设计[J].自动化仪表,2012,33(08)：74-77+80.
[156]李玉凯,白焰,高喜奎.智能分析仪表PROFIBUS-DP接口的研发[J].化工自动化及仪表,2011,38(01)：56-59+64.
[157]叶园,白焰,王仁书.InTouch在无线超滤监控系统中的应用[J].化工自动化及仪表,2012,39(02)：228-231+240.
[158]Heo J., Hong J., Cho Y.. EARQ:Energy Aware Routing for Real-Time and Reliable Communication in Wireless Industrial Sensor Networks [J]. IEEE Transactions on Industrial Informatics,2008,5(1):3-11.
[159]中国电子信息产业发展研究院.2011中国物联网产业发展指南[M].北京：机械工业出版社,2011.
[160]Cavalcanti D, Agrawal D, Cordeiro C, et al. Issues in integrating cellular networks WLANs, AND MANETs:a futuristic heterogeneous wireless network [J]. Wireless Communications, IEEE,2005,12(3):30-41.
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