电力电容器真空浸渍监控系统的设计与实现
摘要
智能控制是在人工智能、认识科学、自动控制和现代控制理论等多学科基础上发展起来的新兴交叉学科,它是自动控制技术的最新发展阶段。现场总线控制系统(FCS)是随着微电子技术、计算机技术、网络技术的发展,并结合先进的控制理论,顺应现代工业控制的要求而发展的产物。它是一种基于现场总线的计算机控制技术,是一种全分散、全数字、全开放的控制系统,特别适用于工业过程控制,制造业及楼宇自动化等领域。是21世纪计算机控制系统的主流。
本文概述了现场总线的概念、体系结构以及特点,分析了几种主要的现场总线。并根据合作单位(桂林市电力电容器有限责任公司)的真空浸渍车间的实际情况,与国外几种常用FCS进行分析比较后,采用基于FCS的智能仪表,设计了基于AIFCS的电力电容器真空浸渍监控系统。该系统既能现场监控,也能远程操作,具有安全可靠,成本低、功能强等特点。
基于AIFCS的真空浸渍监控系统由现场监控层、操作站和远程监控层构成。现场监控层包括有现场智能仪表及总线模块,主要完成现场数据的采集和简单的控制,并通过总线与操作站进行通讯。操作站主要是工业计算机,能实现对各个真空罐的状态进行监控,并执行复杂的数据分析和控制策略。远程控制则是利用基于ARM的技术,在远程利用网络对现场设备进行监控。
现场仪表设计主要包括以AT89S52为CPU的核心模块、显示电路模块、系统存储模块、系统输入输出模块、通讯模块等,本文对主要的功能电路进行详细的分析设计。
系统软件则是以VC++6.0为平台,根据AIBUS协议,自主开发上位机的全部监控系统,其中包括有实时通信系统、仪表设置系统、智能算法系统、数据记录系统、报警系统、历史数据描绘系统以及真空罐工作流程图等。各系统模块独立设计,协调工作。
本文提出一种改进PSO(粒子群优化算法)整定PID的方法,并通过理论分析及仿真,证明方法的有效性。
同时,利用人工智能方法,设计开发了一种结合模糊控制技术的PID控制——模糊自适应PID控制(FAPID)。该控制技术既具有模糊控制自适应能力强,动态特性好的优点,又具备PID控制简单、灵活、静态稳定性好的优点。通过理论分析、仿真以及实际测试,证明该算法不仅控制精度高,过渡时间短,超调量小,而且还具有自适应和自学习功能,具有良好的动态和稳态性能。
通过对仿真和实验测试结果的分析,本系统的各项性能指标均符合电力电容器真空罐浸渍的设计要求,并且具有很好的稳定性和较高的精确度。
Intelligent control is a new interdisciplinary subject based on artificial intelligence, cognitive science, automation, and modern cybernetics, etc. Combining the advanced control theory and adapting the requirement of modern industrious control. Field Control System (FCS) is an outcome of development of microelectronic technology, computer technology, network technology and it is based on the fieldbus. It is a totally scattered, full digital and total opening control system especially suitable to be applied in the fields of industrial process control, manufacturing industry and building automation system. It is a mainstream of computer control system in the 21st century. In this thesis, the structure of FCS and its characteristics are summarized and some major fieldbus products are introduced. After comparing with several abroad fieldbus products and considering the cooperative company (Guilin Power Capacitor Co.Ltd) actual conditions of the vacuum-impregnated workshop, the AIFCS, a product designed by Xiamen Yudian Automation Technology Co.Ltd, is chosen to design a AIFCS-based power capacitor vacuum-impregnated monitoring system. This system can be not only used for field monitoring, but also support remote operation. It possesses the features of safety and reliability, low-cost, powerful function and so on.
The AIFCS-based vacuum-impregnated monitoring system consists of locate monitoring layer, operation station and remote monitoring layer. The locate monitoring layer includes field intelligent instrument and bus module. It’s main functions are to fulfill real-time data collection, implement simple control, and communicate via the bus between devices and operation station. The operation station is IPC(Industrial Personal Computer) which can monitor the condition of every vacuum container and carry out the analysis of complex data and control strategy. Remote control is to use ARM-based technology through the long-distance network to monitor the field devices.
The design of the field instrument mainly includes a core module using AT89S52 as CPU, display circuit module, storing system module, I/O system module, communication module. This thesis aims at analyzing and designing the main functional circuit in detail.
VC++6.0 is used as a tool to set up the software system.The monitoring systems is developed according to AIBUS protocol and it consists of real-time communication system, instrument-setting system, intelligence algorithm system, data recording system, alarm system, historical data description system as well as the working flowchart of vacuum container, etc. Each system module is designed independently and all of them work in coordination.
To tuning PID parameters, Particle Swarm Optimization (PSO) algorithm is used to improve the effect of the system, which is testified both by the theoretical analysis and the system simulation.
At the same time, we design and develop a fuzzy self-adapting PID control system (FAPID) in which fuzzy control technology is adopted. This control system has the advantages of the powerful fuzzy adaptive controlling capability, the good dynamic characteristic, flexibility and the static stability. System simulation and practical tests prove that this algorithm not only has the high control precision, the short transition time, the smaller overshoot, the function of self-adaptation and self-learning, but also has the good dynamic and stable property.
The analysis and simulation results prove that the performance of this system can meet the design requirements and serves the controlling purpose of the power capacitor vacuum container with better stability and higher precision.
本文概述了现场总线的概念、体系结构以及特点,分析了几种主要的现场总线。并根据合作单位(桂林市电力电容器有限责任公司)的真空浸渍车间的实际情况,与国外几种常用FCS进行分析比较后,采用基于FCS的智能仪表,设计了基于AIFCS的电力电容器真空浸渍监控系统。该系统既能现场监控,也能远程操作,具有安全可靠,成本低、功能强等特点。
基于AIFCS的真空浸渍监控系统由现场监控层、操作站和远程监控层构成。现场监控层包括有现场智能仪表及总线模块,主要完成现场数据的采集和简单的控制,并通过总线与操作站进行通讯。操作站主要是工业计算机,能实现对各个真空罐的状态进行监控,并执行复杂的数据分析和控制策略。远程控制则是利用基于ARM的技术,在远程利用网络对现场设备进行监控。
现场仪表设计主要包括以AT89S52为CPU的核心模块、显示电路模块、系统存储模块、系统输入输出模块、通讯模块等,本文对主要的功能电路进行详细的分析设计。
系统软件则是以VC++6.0为平台,根据AIBUS协议,自主开发上位机的全部监控系统,其中包括有实时通信系统、仪表设置系统、智能算法系统、数据记录系统、报警系统、历史数据描绘系统以及真空罐工作流程图等。各系统模块独立设计,协调工作。
本文提出一种改进PSO(粒子群优化算法)整定PID的方法,并通过理论分析及仿真,证明方法的有效性。
同时,利用人工智能方法,设计开发了一种结合模糊控制技术的PID控制——模糊自适应PID控制(FAPID)。该控制技术既具有模糊控制自适应能力强,动态特性好的优点,又具备PID控制简单、灵活、静态稳定性好的优点。通过理论分析、仿真以及实际测试,证明该算法不仅控制精度高,过渡时间短,超调量小,而且还具有自适应和自学习功能,具有良好的动态和稳态性能。
通过对仿真和实验测试结果的分析,本系统的各项性能指标均符合电力电容器真空罐浸渍的设计要求,并且具有很好的稳定性和较高的精确度。
Intelligent control is a new interdisciplinary subject based on artificial intelligence, cognitive science, automation, and modern cybernetics, etc. Combining the advanced control theory and adapting the requirement of modern industrious control. Field Control System (FCS) is an outcome of development of microelectronic technology, computer technology, network technology and it is based on the fieldbus. It is a totally scattered, full digital and total opening control system especially suitable to be applied in the fields of industrial process control, manufacturing industry and building automation system. It is a mainstream of computer control system in the 21st century. In this thesis, the structure of FCS and its characteristics are summarized and some major fieldbus products are introduced. After comparing with several abroad fieldbus products and considering the cooperative company (Guilin Power Capacitor Co.Ltd) actual conditions of the vacuum-impregnated workshop, the AIFCS, a product designed by Xiamen Yudian Automation Technology Co.Ltd, is chosen to design a AIFCS-based power capacitor vacuum-impregnated monitoring system. This system can be not only used for field monitoring, but also support remote operation. It possesses the features of safety and reliability, low-cost, powerful function and so on.
The AIFCS-based vacuum-impregnated monitoring system consists of locate monitoring layer, operation station and remote monitoring layer. The locate monitoring layer includes field intelligent instrument and bus module. It’s main functions are to fulfill real-time data collection, implement simple control, and communicate via the bus between devices and operation station. The operation station is IPC(Industrial Personal Computer) which can monitor the condition of every vacuum container and carry out the analysis of complex data and control strategy. Remote control is to use ARM-based technology through the long-distance network to monitor the field devices.
The design of the field instrument mainly includes a core module using AT89S52 as CPU, display circuit module, storing system module, I/O system module, communication module. This thesis aims at analyzing and designing the main functional circuit in detail.
VC++6.0 is used as a tool to set up the software system.The monitoring systems is developed according to AIBUS protocol and it consists of real-time communication system, instrument-setting system, intelligence algorithm system, data recording system, alarm system, historical data description system as well as the working flowchart of vacuum container, etc. Each system module is designed independently and all of them work in coordination.
To tuning PID parameters, Particle Swarm Optimization (PSO) algorithm is used to improve the effect of the system, which is testified both by the theoretical analysis and the system simulation.
At the same time, we design and develop a fuzzy self-adapting PID control system (FAPID) in which fuzzy control technology is adopted. This control system has the advantages of the powerful fuzzy adaptive controlling capability, the good dynamic characteristic, flexibility and the static stability. System simulation and practical tests prove that this algorithm not only has the high control precision, the short transition time, the smaller overshoot, the function of self-adaptation and self-learning, but also has the good dynamic and stable property.
The analysis and simulation results prove that the performance of this system can meet the design requirements and serves the controlling purpose of the power capacitor vacuum container with better stability and higher precision.
引文
[1] 何大春.无功功率自动补偿控制系统的研究和设计[D]. 南京:南京理工大学,2002.
[2] 房金兰.我国电力电容器及无功补偿装置制造技术的发展[J].电力电容器(无功补偿技术论文集),2006:(1-6).
[3] 祝霆.电力电容器市场预测与产品发展[J].电力电容器,2006,1:41-42.
[4] 阳宪惠.现场总线技术及其应用[M].北京:清华大学出版社,1999.6.
[5] 郝仙庭.FCS 是工业控制系统的发展趋势[J].仪器仪表与分析监测,2004,2:1-3.
[6] 黄生睿,张超.FCS 在火电厂厂用电控制系统的应用[J].电力建设,2006,27(6):39-41.
[7] 刘先广,华陈权.FCS 在热媒炉控制中的应用[J].化工自动化及仪表,2002,29(4):67-69.
[8] Andrew S.Tanenbaum.COMPUTER NETWORKS[M].北京:清华大学出版社,2005,1.
[9] 章剑雄,冯浩.现场总线技术概述[J].自动化与仪表,2002,6:1-4.
[10] 刘紫燕,冯丽.现场总线技术与现场总线控制系统[J].现代机械,2002(3):1-3.
[11] Peter Neumann.Communication in industrial automation—What is going on?[J]. Control Engineering Practice, 2007,15(11): 1332-1347.
[12] 王杰.现场总线技术的现状与发展[J].电气传动自动化,2005,27(3):15-19.
[13] 王富善,平东波.浅谈现场总线及现场总线控制系统[J].中国仪器仪表,2001,34(5): 66 一 68.
[14] 黄志辉,张利,龙赛琼.基于 RS-485 现场总线的机床监测系统设计[J].控制与检测,2005(10):39～41.
[15] 尤天刚.基于 ARM 的嵌人式工控网络平台的构建[D].成都:电子科技大学,2006.
[16] 王常力.现场总线与 DCS:讨论与实践[J].自动化博览,1999(5):1-7.
[17] AIFCS 计算机监控系统.http://www.yudian.com.
[18] 迟岩,黄种明,卢丽萍.基于 AIFCS 工业配电智能化监控系统设计[J].辽宁工程技术大学学报,2006 25(1):76-79.
[19] 孙育才,王荣兴,孙华芳.ATME 新型 AT89S52 系列单片机及其应用[M].北京:清华大学出版社,2005.
[20] 宁起超 , 邵国平 , 赵洪涛 . 基于 AT89S52 的温度控制器的设计 [J]. 黑龙江工程学院学报2006,21(1):54-56.
[21] 胡汉才.单片机原理及接口技术[M].北京:清华大学出版社,1996.
[22] 余永权.ATMEL89 系列单片机应用技术[M].北京:北京航空航天大学出版社,2002.
[23] 刘绿山,刘建群,李仕勇.基于 AT89S52 单片机的温度控制系统[J].微计算机信息,2007,23(62):98-100.
[24] 杨帮文.最新传感器应用手册[M].北京:人民邮电出版社,2004.
[25] 纪宗南.单片机外围器件手册-输入通道器件分册(第二版)[M].北京:北京航空航天大学出版社,2005.
[26] 乌宽明.单片机外围器件手册-数据传输接口器件分册(第二版)[M].北京:北京航空航天大学出版社,2005.
[27] AIBUS 通讯协议说明(V7.0).厦门宇电科技,2006.
[28] 用 VC 6.0 实现串行通信的三种方法.http://tech.163.com.
[29] 李闽溟,吴继刚,周学明.Visual C++6.0 数据库系统开发实例导航[M].北京:人民出版社,2003.
[30] 祝小斌. mschart 示例.http://www.vckbase.com.
[31] 杜春雷.ARM 体系结构与编程[M].北京:清华大学出版社,2006.
[32] 孙天泽,袁文菊.嵌入式设计及 Linux 驱动开发指南-基于 ARM9 处理器(第 2 版)[M].北京:电子工业出版社,2007.
[33] 陶永华.新型 PID 控制及其应用[M].北京:机械工业出版社,2003.
[34] 王伟,张晶涛,柴天佑.PID 参数先进整定方法综述[J].自动化学报,2000,26(3):347-353.
[35] 蒋新华.自适应 PID 控制[J].信息与控制,1988,17(5):41-49.
[36] 刘金馄.先进 PID 控制及其 MATLAB 仿真.北京:电子工业出版社,2003.
[37] 吴宏鑫,沈少萍.PID 控制的应用与理论依据[J].控制工程,2003,10(1):38-42.
[38] 孙林军.智能 PID 控制的研究[D].浙江:浙江工业大学,2003.
[39] 李银伢.满意 PID 控制器设计理论[D].南京:南京理工大学,2006.
[40] Ziegler J G, Nichols N B. Optimum settings for automatic controllers. Trans. ASME, 1942,64:759-768.
[41] D P Kwok, F Sheng. Genetic algorithm and simulated annealing for optimal robot arm PID control [C].Proc IEEE Conf. Evol. Comput, Orlando, FL, 1994, 707-713.
[42] D B Fogel. Evolutionary Computation: Toward a New Philosophy of Machine Intelligence [M]. New York: IEEE Press, 2000.
[43] J Kennedy, R Eberhart. Particle Swarm Optimization [C].Proc. IEEE Int. Conf. Neural Networks, 1995:1942-1948.
[44] Z L Gaing. A Particle Swarm Optimisation Approach for Optimum Design of PID Controller in AVR System [J] IEEE Trans. on Energy Conversion (S0885-8969), 2004,19(2): 384-391.
[45] Y Shi, R C Eberhart. A modified swarm optimizer[A].IEEE International Conference of Evolutionary Computation[C].Anchorage,Alaska:IEEE Press, May,1998.
[46] 郭柄辉,李进京.温室智能测控系统模糊控制器设计[J].山东农机,2003.12(10):10-11.
[47] Zhi-Wei Woo, Hung-Yuan Chung, Jin-Jye Lin .A PID type fuzzy controller with self-tuning scaling factors[J]. Fuzzy Sets and Systems ,2000(115) :321-326.
[48] Edgar N. Sancheza, Hector M. Becerraa, Carlos M. Velezb.Combining fuzzy, PID and regulation control foran autonomous mini-helicopter[J]. Information Sciences,2007(177): 1999–2022.
[49] 孙频东.回转窑模糊控制系统[J].信息技术.2002(10):9-11.
[50] 孙增圻.智能控制理论与技术[M].北京:清华大学出版社,2004.
[51] Yau-Tarng Juanga, Yun-Tien Changa, Chih-Peng Huangb.Design of fuzzy PID controllers using modified triangular membership functions[J]. Information Sciences, 2008(178): 1325–1333.
[52] Zhijun Suna, Rentao Xinga, Chunsheng Zhaob, Weiqing Huangb.Fuzzy auto-tuning PID control of multiple joint robot drivenby ultrasonic motors[J]. Ultrasonics ,2007(46 ):303–312.
[53] J.N. Lygourasa, P.N. Botsarisb, J. Vourvoulakisa,V. Kodogiannisc. Fuzzy logic controller implementation for a solarair-conditioning system[J]. Applied Energy,2007(84):1305–1318.
[54] S.E.Mansour,G. C. Kember,R. Dubay, B. Robertson.Online optimization of fuzzy-PID control of a thermal process[J]. ISA Transactions,2005( 44):305–314.
[55] Jialiang Lu, Guanrong Chen, Hao Ying.Predictive fuzzy PID control: theory,design and simulation[J]. Information Sciences ,2001(137):157-187.
[2] 房金兰.我国电力电容器及无功补偿装置制造技术的发展[J].电力电容器(无功补偿技术论文集),2006:(1-6).
[3] 祝霆.电力电容器市场预测与产品发展[J].电力电容器,2006,1:41-42.
[4] 阳宪惠.现场总线技术及其应用[M].北京:清华大学出版社,1999.6.
[5] 郝仙庭.FCS 是工业控制系统的发展趋势[J].仪器仪表与分析监测,2004,2:1-3.
[6] 黄生睿,张超.FCS 在火电厂厂用电控制系统的应用[J].电力建设,2006,27(6):39-41.
[7] 刘先广,华陈权.FCS 在热媒炉控制中的应用[J].化工自动化及仪表,2002,29(4):67-69.
[8] Andrew S.Tanenbaum.COMPUTER NETWORKS[M].北京:清华大学出版社,2005,1.
[9] 章剑雄,冯浩.现场总线技术概述[J].自动化与仪表,2002,6:1-4.
[10] 刘紫燕,冯丽.现场总线技术与现场总线控制系统[J].现代机械,2002(3):1-3.
[11] Peter Neumann.Communication in industrial automation—What is going on?[J]. Control Engineering Practice, 2007,15(11): 1332-1347.
[12] 王杰.现场总线技术的现状与发展[J].电气传动自动化,2005,27(3):15-19.
[13] 王富善,平东波.浅谈现场总线及现场总线控制系统[J].中国仪器仪表,2001,34(5): 66 一 68.
[14] 黄志辉,张利,龙赛琼.基于 RS-485 现场总线的机床监测系统设计[J].控制与检测,2005(10):39～41.
[15] 尤天刚.基于 ARM 的嵌人式工控网络平台的构建[D].成都:电子科技大学,2006.
[16] 王常力.现场总线与 DCS:讨论与实践[J].自动化博览,1999(5):1-7.
[17] AIFCS 计算机监控系统.http://www.yudian.com.
[18] 迟岩,黄种明,卢丽萍.基于 AIFCS 工业配电智能化监控系统设计[J].辽宁工程技术大学学报,2006 25(1):76-79.
[19] 孙育才,王荣兴,孙华芳.ATME 新型 AT89S52 系列单片机及其应用[M].北京:清华大学出版社,2005.
[20] 宁起超 , 邵国平 , 赵洪涛 . 基于 AT89S52 的温度控制器的设计 [J]. 黑龙江工程学院学报2006,21(1):54-56.
[21] 胡汉才.单片机原理及接口技术[M].北京:清华大学出版社,1996.
[22] 余永权.ATMEL89 系列单片机应用技术[M].北京:北京航空航天大学出版社,2002.
[23] 刘绿山,刘建群,李仕勇.基于 AT89S52 单片机的温度控制系统[J].微计算机信息,2007,23(62):98-100.
[24] 杨帮文.最新传感器应用手册[M].北京:人民邮电出版社,2004.
[25] 纪宗南.单片机外围器件手册-输入通道器件分册(第二版)[M].北京:北京航空航天大学出版社,2005.
[26] 乌宽明.单片机外围器件手册-数据传输接口器件分册(第二版)[M].北京:北京航空航天大学出版社,2005.
[27] AIBUS 通讯协议说明(V7.0).厦门宇电科技,2006.
[28] 用 VC 6.0 实现串行通信的三种方法.http://tech.163.com.
[29] 李闽溟,吴继刚,周学明.Visual C++6.0 数据库系统开发实例导航[M].北京:人民出版社,2003.
[30] 祝小斌. mschart 示例.http://www.vckbase.com.
[31] 杜春雷.ARM 体系结构与编程[M].北京:清华大学出版社,2006.
[32] 孙天泽,袁文菊.嵌入式设计及 Linux 驱动开发指南-基于 ARM9 处理器(第 2 版)[M].北京:电子工业出版社,2007.
[33] 陶永华.新型 PID 控制及其应用[M].北京:机械工业出版社,2003.
[34] 王伟,张晶涛,柴天佑.PID 参数先进整定方法综述[J].自动化学报,2000,26(3):347-353.
[35] 蒋新华.自适应 PID 控制[J].信息与控制,1988,17(5):41-49.
[36] 刘金馄.先进 PID 控制及其 MATLAB 仿真.北京:电子工业出版社,2003.
[37] 吴宏鑫,沈少萍.PID 控制的应用与理论依据[J].控制工程,2003,10(1):38-42.
[38] 孙林军.智能 PID 控制的研究[D].浙江:浙江工业大学,2003.
[39] 李银伢.满意 PID 控制器设计理论[D].南京:南京理工大学,2006.
[40] Ziegler J G, Nichols N B. Optimum settings for automatic controllers. Trans. ASME, 1942,64:759-768.
[41] D P Kwok, F Sheng. Genetic algorithm and simulated annealing for optimal robot arm PID control [C].Proc IEEE Conf. Evol. Comput, Orlando, FL, 1994, 707-713.
[42] D B Fogel. Evolutionary Computation: Toward a New Philosophy of Machine Intelligence [M]. New York: IEEE Press, 2000.
[43] J Kennedy, R Eberhart. Particle Swarm Optimization [C].Proc. IEEE Int. Conf. Neural Networks, 1995:1942-1948.
[44] Z L Gaing. A Particle Swarm Optimisation Approach for Optimum Design of PID Controller in AVR System [J] IEEE Trans. on Energy Conversion (S0885-8969), 2004,19(2): 384-391.
[45] Y Shi, R C Eberhart. A modified swarm optimizer[A].IEEE International Conference of Evolutionary Computation[C].Anchorage,Alaska:IEEE Press, May,1998.
[46] 郭柄辉,李进京.温室智能测控系统模糊控制器设计[J].山东农机,2003.12(10):10-11.
[47] Zhi-Wei Woo, Hung-Yuan Chung, Jin-Jye Lin .A PID type fuzzy controller with self-tuning scaling factors[J]. Fuzzy Sets and Systems ,2000(115) :321-326.
[48] Edgar N. Sancheza, Hector M. Becerraa, Carlos M. Velezb.Combining fuzzy, PID and regulation control foran autonomous mini-helicopter[J]. Information Sciences,2007(177): 1999–2022.
[49] 孙频东.回转窑模糊控制系统[J].信息技术.2002(10):9-11.
[50] 孙增圻.智能控制理论与技术[M].北京:清华大学出版社,2004.
[51] Yau-Tarng Juanga, Yun-Tien Changa, Chih-Peng Huangb.Design of fuzzy PID controllers using modified triangular membership functions[J]. Information Sciences, 2008(178): 1325–1333.
[52] Zhijun Suna, Rentao Xinga, Chunsheng Zhaob, Weiqing Huangb.Fuzzy auto-tuning PID control of multiple joint robot drivenby ultrasonic motors[J]. Ultrasonics ,2007(46 ):303–312.
[53] J.N. Lygourasa, P.N. Botsarisb, J. Vourvoulakisa,V. Kodogiannisc. Fuzzy logic controller implementation for a solarair-conditioning system[J]. Applied Energy,2007(84):1305–1318.
[54] S.E.Mansour,G. C. Kember,R. Dubay, B. Robertson.Online optimization of fuzzy-PID control of a thermal process[J]. ISA Transactions,2005( 44):305–314.
[55] Jialiang Lu, Guanrong Chen, Hao Ying.Predictive fuzzy PID control: theory,design and simulation[J]. Information Sciences ,2001(137):157-187.
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