基于Petri网的智能控制系统建模仿真与性能分析
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摘要
随着人们探索自然领域的拓展,控制系统的规模日益扩大,复杂程度逐渐增加。对系统进行建模、仿真和分析是对系统进行进一步设计实现的基础,其研究具有非常重要的意义。智能控制系统通常具有分层结构,各模块之间的信息可能是定量信息,也可能是定性信息,有时还有可能出现模糊随机的时变信息。因此,无论在系统行为特征还是控制策略方面,都体现了其复杂性和不确定性。通常,智能控制系统是一个异步并发系统,而Petri网刚好在描述分析异步并发系统方面具有独特优势。Petri网是一种图形化的语言,具有强大的描述、分析复杂系统的能力。Petri网可以把复杂问题转化为更简单清晰的图形,能够精确描述事件的顺序、异步、并发和冲突关系,既能表达系统静态结构又能对系统进行动态行为分析。因此,Petri网非常适合用于对智能控制系统进行建模和分析。
本文选用智能电梯系统作为研究对象,建立基于Petri网的仿真模型。针对智能电梯系统的需求和特点,通过在基本Petri网中引入分层、时间和颜色的概念,采用一种复合高级Petri网——分层时间有色Petri网(Hierarchical Timed Colored Petri Nets,以下简称HTCPN)来建立智能电梯群控系统的HTCPN模型。该模型解决了采用基本Petri网建模节点过多,状态空间爆炸,没有时序等问题。然后,选择CPN主流仿真工具CPN Tools作为构建HTCPN模型的工具。结合该工具中替代变迁与融合库所的概念,对智能电梯控制电路进行了分层建模和融合,完成了基于HTCPN的智能电梯控制电路仿真模型。最后通过模型的仿真运行,分析了模型的相关性能,验证了该模型的正确性和可行性。通过与非并联控制的双梯单独服务情况的对比,得出采用双梯并联控制实现了对系统的优化。
As the expansion of natural areas people explored, the scale of control system is getting larger and larger, and its complexity is increasing gradually. Establishing a simulating model for system analysis is the basis for further design and implementation. This research is very significant now. Intelligent control systems usually have a hierarchical structure. The information between the modules may be quantitative information, qualitative information, or sometimes may be fuzzy random time-varying information. Therefore, both the behavioral characteristics and control strategy of the system is complex and uncertain. Usually, the intelligent control system is an asynchronous concurrent system. Petri net just has a unique advantage for describing the asynchronous concurrent systems. Petri net is a graphical language. It’s a powerful tool for describing and analyzing the complex systems. The complex issues can be transformed into more simple and clearer graphics by Petri nets. Petri nets can accurately describe the relationship between the events, such as sequence, asynchronous, concurrent, conflict, etc.. It can both express the static structure of the system and analyze the dynamic behavior of the system. Therefore, Petri nets are fairly suitable for modeling and analyzing the intelligent control systems.
This paper selected intelligent elevator system as the research object, established simulation model based on Petri nets. In view of the needs and characteristics of intelligent elevator system, introduced concepts of hierarchy, time and color to the basic Petri nets. Used a composite high-level Petri nets - Hierarchical Timed Colored Petri nets (hereinafter referred to as HTCPN) to create HTCPN model of intelligent elevator group control system. The model solves the problem of too many nodes, state space explosion, no timing and other issues based on basic Petri net model. Then, selected the mainstream simulation tool CPN Tools for establishing HTCPN model. With its modeling techniques of substitution transition and fusion place, established an HTCPN model of intelligent elevator control circuit. Finally, by simulation running of the model, analyzed the relative performance of the model, verified the correctness and feasibility of the model. By contrast with the situation of non-parallel control system providing a separate service, the elevator system which adopted the parallel control strategy achieved a better performance.
本文选用智能电梯系统作为研究对象,建立基于Petri网的仿真模型。针对智能电梯系统的需求和特点,通过在基本Petri网中引入分层、时间和颜色的概念,采用一种复合高级Petri网——分层时间有色Petri网(Hierarchical Timed Colored Petri Nets,以下简称HTCPN)来建立智能电梯群控系统的HTCPN模型。该模型解决了采用基本Petri网建模节点过多,状态空间爆炸,没有时序等问题。然后,选择CPN主流仿真工具CPN Tools作为构建HTCPN模型的工具。结合该工具中替代变迁与融合库所的概念,对智能电梯控制电路进行了分层建模和融合,完成了基于HTCPN的智能电梯控制电路仿真模型。最后通过模型的仿真运行,分析了模型的相关性能,验证了该模型的正确性和可行性。通过与非并联控制的双梯单独服务情况的对比,得出采用双梯并联控制实现了对系统的优化。
As the expansion of natural areas people explored, the scale of control system is getting larger and larger, and its complexity is increasing gradually. Establishing a simulating model for system analysis is the basis for further design and implementation. This research is very significant now. Intelligent control systems usually have a hierarchical structure. The information between the modules may be quantitative information, qualitative information, or sometimes may be fuzzy random time-varying information. Therefore, both the behavioral characteristics and control strategy of the system is complex and uncertain. Usually, the intelligent control system is an asynchronous concurrent system. Petri net just has a unique advantage for describing the asynchronous concurrent systems. Petri net is a graphical language. It’s a powerful tool for describing and analyzing the complex systems. The complex issues can be transformed into more simple and clearer graphics by Petri nets. Petri nets can accurately describe the relationship between the events, such as sequence, asynchronous, concurrent, conflict, etc.. It can both express the static structure of the system and analyze the dynamic behavior of the system. Therefore, Petri nets are fairly suitable for modeling and analyzing the intelligent control systems.
This paper selected intelligent elevator system as the research object, established simulation model based on Petri nets. In view of the needs and characteristics of intelligent elevator system, introduced concepts of hierarchy, time and color to the basic Petri nets. Used a composite high-level Petri nets - Hierarchical Timed Colored Petri nets (hereinafter referred to as HTCPN) to create HTCPN model of intelligent elevator group control system. The model solves the problem of too many nodes, state space explosion, no timing and other issues based on basic Petri net model. Then, selected the mainstream simulation tool CPN Tools for establishing HTCPN model. With its modeling techniques of substitution transition and fusion place, established an HTCPN model of intelligent elevator control circuit. Finally, by simulation running of the model, analyzed the relative performance of the model, verified the correctness and feasibility of the model. By contrast with the situation of non-parallel control system providing a separate service, the elevator system which adopted the parallel control strategy achieved a better performance.
引文
[1]蔡自兴.智能控制原理与应用[M].北京:清华大学出版社,2007.
[2]康爱红.复杂系统的智能控制建模与控制方法研究[D].苏州理工大学,2004.
[3] Randolph M. Jones, John E. Laird, Paul E. Nielsen, Karen J. Coulter, Patrick Kenny, Frank V. Koss. Automated Intelligent Pilots for Combat Flight Simulation[J]. AI Magazine Volume 20 Number 1,1999.
[4] C.A.Petri. Kommunikation mit Automaten[D]. Bonn, West Germany: University of Bonn,1962 .
[5]蒋昌俊.Petri网的行为理论及其应用[M].北京:高等教育出版社,2003.
[6] Kurt Jensen, Lars Michael Kristensen, Lisa Wells. Colored Petri Nets and CPN Tools for Modeling and Validation of Concurrent Systems [J]. Int J Softw Toolstechnol Transfer,2007,9:213-254.
[7]林闯.随机Petri网和系统性能评价[M].北京:清华大学出版社,2000.
[8]林琳,李宏光.基于Petri网的混杂系统监控与诊断方法[J].微计算机应用2005,26(4).
[9]袁崇义.Petri网原理与应用.北京:电子工业出版社,2005.
[10] Tiehua Cao, Arthur C. Sanderson .Intelligent task planning using fuzzy Petri nets[M]. Pinted in Singapore by Uto-Print.1996.
[11] Guo-Yan Huang. Analysis of Artificial Intelligence Based Petri Net Approach to Intelligent Integration of Design[J]. International Conference on Machine Learning and Cybernetics,2010.
[12]徐立云,张春慨,邵惠鹤.基于Petri网的一种事实计划调度方法[J].上海交通大学学报,2001(11).
[13]王卡停.柔性制造系统的Petri网物流仿真[D].浙江大学,2001.
[14]朱华炳.制造业生产物流系统规划与调度技术研究[D].合肥工业大学,2005.
[15]刘婷,林闯,刘卫东.基于时间Petri网的工作流系统模型的线性推理[J].电子学报,2002(02).
[16]曲扬.基于Petri网的工作流建模和分析方法研究[D].清华大学,2004.
[17]姜浩,罗军舟,方宁生.模糊Petri网在带权不精确知识表示的推理中的应用研究[J].计算机研究与发展,2000(08).
[18]蒋元凯,韩冰.启发式搜索在时间Petri网的共享资源调度中的应用[J].微型电脑应用,2000(12):35～38.
[19]胡红革.网络化控制系统Petri网建模方法与分析[D].电子科技大学,2004.
[20]宗群,窦立谦,程义菊.基于时间_有色Petri网的电梯系统的建模与分析[J].中国工程科学,2004(12)Vol.6.
[21]顾明甲.基于网络协议的Petri网研究[D].江南大学,2009.12.
[22]林闯,杨士强.多服务器多队列系统调度方案的性能分析[J].电子学报,2000(5):17～2.
[23] Junfeng Wang, Jianhua Yang, Gaogang Xie, Mingtian Zhou. OSPFv3 Protocol Simulation with Colored Petri Nets[A]. Proceedings of 2003 International Conference on Communication Technology Volume 1 of 2[C], 2003.
[24]左凤朝.基于Petri网的数据库系统并发控制模型[J] .计算机工程与应用,2002(13).
[25]左凤朝.基于Petri网的数据库系统并发控制活性分析[J].计算机工程与应用,2002,(17).
[26]贺细平,乐晓波.主动数据库规则集的Petri网建模[J].计算机工程与设计, 2008,(02).
[27] L. E. Holloway, B. H. Krogh and A. Giua. A Survey of Petri Net Methods for Controlled Discrete Event Systems[A]. Discrete Event Dynamic Systems: Theory and Applications,1997,7:151–190.
[28] Moody J O, Antsaklis P J, Petri Net Supervisors for DES with uncontrollable and unobservable transitions[J]. Automatic Control, IEEE Transactions on Automatic Control,2000,3: 462– 476.
[29]胡昌华,王青,陈新海.基于Petri网的导弹控制系统故障诊断梯形图求解法[J] ,宁航学报,2001(01).
[30]张明.智能PID控制的仿真研究与工程应用[D].华中科技大学,2006.
[31] Flies M, Join C.Intelligent PID controllers[J].2008 Mediterranean conference on control and automation,2008,6:326-331.
[32]田华,蒋慰孙.一种专家控制器——设计原理和比较研究[J].信息与控制, 1990(03).
[33]魏红昀,邓忠华,魏晴昀.PID专家控制器在温控系统中的应用[J].兵工自动化, 2005(08).
[34]金耀.自适应单神经元智能控制策略及其在汽车主动悬架中的应用研究[D].湖南大学,2008(4).
[35]许力.连续搅拌反应器的实时智能控制[D].浙江大学, 2006.
[36]许家民.基于传感器的加工过程智能控制技术研究[D].河海大学, 2007.
[37]刘研.改进遗传算法及在电器产品优化设计中的研究[D].沈阳工业大学, 2007.
[38] William Burke, David Auslander. PWM Synchronization for Intelligent Agent Scarce Resource Auction[J]. ASME 2009 Dynamic Systems and Control Conference Hollywood, California 2009,10,14.
[39]燕必成.基于Petri网的足球机器人决策子系统的研究[D].西安电子科技大学,2007.
[40]辛晓乐.基于Petri网的化工过程智能控制系统[D].北京化工大学, 2008.
[41]叶阳东.智能混杂系统建模分析理论及应用的研究[D].铁道部科学研究院, 2002.
[42]蒋昌俊.Petri网的行为理论及其应用[M].北京:高等教育出版社,2003.
[43]袁崇义.Petri网原理[M].北京:电子工业出版社,1998.
[44] J. Niu, J. Zou (USA), and A. Ren (PRC). OOPN: Object-oriented Petri Nets and Its Integrated Development Environment[J]. Proceeding (397) Software Engineering and Applications,2003.
[45] Looney C G.. Fuzzy Petri nets for rule-based decision making[J]. IEEE Transactions on Systems, Man and Cybernetics,2002(8).
[46] Ciardo G., Muppala J, Trivedi K. SPNP: Stochastic Petri Net Package[J]. Proceedings of the Third International Workshop on Petri Nets and Performance Models,1989.
[47] D Kartson, G. Balbo, S Donatelli, G. Franceschinis. Modeling with Generalized Stochastic Petri Nets[M]. John Wiley & Sons, Inc. New York, NY, USA ?1994
[48] Tadao Murata. Petri Nets: Properties. Analysis and Applications[J]. Proceedings of The IEEE, Vol.77, No.4, April 1989.
[49] R S Srinivasan. Modeling and Performance Analysis of Cluster Tools Using Petri Nets[J]. IEEE Transactions on Semiconductor Manufacturing, Vol. 11, No.3, August 1998; 394-399.
[50] Shadi Rostami, Babak Hamidzadeh, Dan Camporese. An Optimal Periodic Scheduler for Dual-Arm Robots in Cluster Tools with Residency Constraints[J]. IEEE Transactions on Robotics And Automation, Vol. 17, No. 5, October 2001.
[51]张乐伟.基于赋时分层着色Petri网的工作流建模与性能评价[D].中国石油大学,2009.
[52] Lisa Wells. Performance analysis using CPN tools[J]. Proceedings of the 1st international conference on Performance evaluation methodologies and tools.October, 2006.
[53] http://cpntools.org/
[54] L Wells. Performance Analysis Using Colored Petri Nets[J]. Proceedings of the 10th IEEE International Symposium on Modeling Analysis, and Simulation of Computer and Telecommunications Systems, 2002.
[55]朱连章,随瑞升,孔莹莹.基于CPN Tools的性能评价仿真研究[J].微计算机应用,2008.
[56] K Jensen, L M Kristensen.Colored Petri Nets. Springer-Verlag Berlin Heidelberg 2009.
[2]康爱红.复杂系统的智能控制建模与控制方法研究[D].苏州理工大学,2004.
[3] Randolph M. Jones, John E. Laird, Paul E. Nielsen, Karen J. Coulter, Patrick Kenny, Frank V. Koss. Automated Intelligent Pilots for Combat Flight Simulation[J]. AI Magazine Volume 20 Number 1,1999.
[4] C.A.Petri. Kommunikation mit Automaten[D]. Bonn, West Germany: University of Bonn,1962 .
[5]蒋昌俊.Petri网的行为理论及其应用[M].北京:高等教育出版社,2003.
[6] Kurt Jensen, Lars Michael Kristensen, Lisa Wells. Colored Petri Nets and CPN Tools for Modeling and Validation of Concurrent Systems [J]. Int J Softw Toolstechnol Transfer,2007,9:213-254.
[7]林闯.随机Petri网和系统性能评价[M].北京:清华大学出版社,2000.
[8]林琳,李宏光.基于Petri网的混杂系统监控与诊断方法[J].微计算机应用2005,26(4).
[9]袁崇义.Petri网原理与应用.北京:电子工业出版社,2005.
[10] Tiehua Cao, Arthur C. Sanderson .Intelligent task planning using fuzzy Petri nets[M]. Pinted in Singapore by Uto-Print.1996.
[11] Guo-Yan Huang. Analysis of Artificial Intelligence Based Petri Net Approach to Intelligent Integration of Design[J]. International Conference on Machine Learning and Cybernetics,2010.
[12]徐立云,张春慨,邵惠鹤.基于Petri网的一种事实计划调度方法[J].上海交通大学学报,2001(11).
[13]王卡停.柔性制造系统的Petri网物流仿真[D].浙江大学,2001.
[14]朱华炳.制造业生产物流系统规划与调度技术研究[D].合肥工业大学,2005.
[15]刘婷,林闯,刘卫东.基于时间Petri网的工作流系统模型的线性推理[J].电子学报,2002(02).
[16]曲扬.基于Petri网的工作流建模和分析方法研究[D].清华大学,2004.
[17]姜浩,罗军舟,方宁生.模糊Petri网在带权不精确知识表示的推理中的应用研究[J].计算机研究与发展,2000(08).
[18]蒋元凯,韩冰.启发式搜索在时间Petri网的共享资源调度中的应用[J].微型电脑应用,2000(12):35～38.
[19]胡红革.网络化控制系统Petri网建模方法与分析[D].电子科技大学,2004.
[20]宗群,窦立谦,程义菊.基于时间_有色Petri网的电梯系统的建模与分析[J].中国工程科学,2004(12)Vol.6.
[21]顾明甲.基于网络协议的Petri网研究[D].江南大学,2009.12.
[22]林闯,杨士强.多服务器多队列系统调度方案的性能分析[J].电子学报,2000(5):17～2.
[23] Junfeng Wang, Jianhua Yang, Gaogang Xie, Mingtian Zhou. OSPFv3 Protocol Simulation with Colored Petri Nets[A]. Proceedings of 2003 International Conference on Communication Technology Volume 1 of 2[C], 2003.
[24]左凤朝.基于Petri网的数据库系统并发控制模型[J] .计算机工程与应用,2002(13).
[25]左凤朝.基于Petri网的数据库系统并发控制活性分析[J].计算机工程与应用,2002,(17).
[26]贺细平,乐晓波.主动数据库规则集的Petri网建模[J].计算机工程与设计, 2008,(02).
[27] L. E. Holloway, B. H. Krogh and A. Giua. A Survey of Petri Net Methods for Controlled Discrete Event Systems[A]. Discrete Event Dynamic Systems: Theory and Applications,1997,7:151–190.
[28] Moody J O, Antsaklis P J, Petri Net Supervisors for DES with uncontrollable and unobservable transitions[J]. Automatic Control, IEEE Transactions on Automatic Control,2000,3: 462– 476.
[29]胡昌华,王青,陈新海.基于Petri网的导弹控制系统故障诊断梯形图求解法[J] ,宁航学报,2001(01).
[30]张明.智能PID控制的仿真研究与工程应用[D].华中科技大学,2006.
[31] Flies M, Join C.Intelligent PID controllers[J].2008 Mediterranean conference on control and automation,2008,6:326-331.
[32]田华,蒋慰孙.一种专家控制器——设计原理和比较研究[J].信息与控制, 1990(03).
[33]魏红昀,邓忠华,魏晴昀.PID专家控制器在温控系统中的应用[J].兵工自动化, 2005(08).
[34]金耀.自适应单神经元智能控制策略及其在汽车主动悬架中的应用研究[D].湖南大学,2008(4).
[35]许力.连续搅拌反应器的实时智能控制[D].浙江大学, 2006.
[36]许家民.基于传感器的加工过程智能控制技术研究[D].河海大学, 2007.
[37]刘研.改进遗传算法及在电器产品优化设计中的研究[D].沈阳工业大学, 2007.
[38] William Burke, David Auslander. PWM Synchronization for Intelligent Agent Scarce Resource Auction[J]. ASME 2009 Dynamic Systems and Control Conference Hollywood, California 2009,10,14.
[39]燕必成.基于Petri网的足球机器人决策子系统的研究[D].西安电子科技大学,2007.
[40]辛晓乐.基于Petri网的化工过程智能控制系统[D].北京化工大学, 2008.
[41]叶阳东.智能混杂系统建模分析理论及应用的研究[D].铁道部科学研究院, 2002.
[42]蒋昌俊.Petri网的行为理论及其应用[M].北京:高等教育出版社,2003.
[43]袁崇义.Petri网原理[M].北京:电子工业出版社,1998.
[44] J. Niu, J. Zou (USA), and A. Ren (PRC). OOPN: Object-oriented Petri Nets and Its Integrated Development Environment[J]. Proceeding (397) Software Engineering and Applications,2003.
[45] Looney C G.. Fuzzy Petri nets for rule-based decision making[J]. IEEE Transactions on Systems, Man and Cybernetics,2002(8).
[46] Ciardo G., Muppala J, Trivedi K. SPNP: Stochastic Petri Net Package[J]. Proceedings of the Third International Workshop on Petri Nets and Performance Models,1989.
[47] D Kartson, G. Balbo, S Donatelli, G. Franceschinis. Modeling with Generalized Stochastic Petri Nets[M]. John Wiley & Sons, Inc. New York, NY, USA ?1994
[48] Tadao Murata. Petri Nets: Properties. Analysis and Applications[J]. Proceedings of The IEEE, Vol.77, No.4, April 1989.
[49] R S Srinivasan. Modeling and Performance Analysis of Cluster Tools Using Petri Nets[J]. IEEE Transactions on Semiconductor Manufacturing, Vol. 11, No.3, August 1998; 394-399.
[50] Shadi Rostami, Babak Hamidzadeh, Dan Camporese. An Optimal Periodic Scheduler for Dual-Arm Robots in Cluster Tools with Residency Constraints[J]. IEEE Transactions on Robotics And Automation, Vol. 17, No. 5, October 2001.
[51]张乐伟.基于赋时分层着色Petri网的工作流建模与性能评价[D].中国石油大学,2009.
[52] Lisa Wells. Performance analysis using CPN tools[J]. Proceedings of the 1st international conference on Performance evaluation methodologies and tools.October, 2006.
[53] http://cpntools.org/
[54] L Wells. Performance Analysis Using Colored Petri Nets[J]. Proceedings of the 10th IEEE International Symposium on Modeling Analysis, and Simulation of Computer and Telecommunications Systems, 2002.
[55]朱连章,随瑞升,孔莹莹.基于CPN Tools的性能评价仿真研究[J].微计算机应用,2008.
[56] K Jensen, L M Kristensen.Colored Petri Nets. Springer-Verlag Berlin Heidelberg 2009.