智能DCS在台车式燃气热处理炉控制中的应用研究
|
摘要
热处理炉在工业生产中有着广泛的应用,本文结合先进控制技术,对热处理炉生产过程控制系统进行了较深入研究,设计了一套软硬件结合的热处理炉生产过程智能集散控制监控系统(DCS)。
本文根据热处理炉的工艺流程和特点,在监控系统整体设计上采用工控机(IPC)+PLC+Profibus-DP现场总线的方案,将系统分为现场执行层、中间控制层和系统管理监控层。现场执行层主要完成现场数据的采集,现场仪表和执行机构的控制功能。中间控制层为PLC控制站和智能温控仪,PLC控制站主要完成基本的逻辑控制功能,实现特殊控制算法。系统管理与监控层由一台IPC组成,通过与PLC、智能温控仪通信来获取生产过程的数据,显示工艺流程、报警画面,实现远程监控。
在系统设计中,热处理炉温控系统作为一个多变量耦合的非线性系统,是控制的难点。通过对其特性进行分析,根据功能区分的原则,将温控系统分成燃烧、燃空比控制、炉膛压力三个回路进行控制,并在主要回路中采用反馈控制系统的方案。同时考虑到热处理炉属于大延迟、非线性时变对象,在温度控制回路中采用了智能控制算法,设计了参数自整定FUZZY-PID控制器,实现了系统控制方案的优化。
为了提高系统设计的准确性,寻找控制系统的最佳结构和参数,本文采用引入辅助变量的改进最小二乘法对温度控制回路建立了数学模型,并用MATLAB对建立的模型分别进行了PID控制方法和模糊控制方法的仿真。仿真结果比较表明,改进的设计方案具有较高控制精度和较好的鲁棒性。
The heat treatment kiln is widely used in industrial production. This paper gives a comprehensive research on kiln production process control system, and designs a set of intelligent monitor and distributed control system(DCS) in the the heat treatment kiln manufacturing process combined hardware with software.
According to the technical flow and characters of heat treatment kiln, the control system was divided into locale layer, middle control layer, and system management layer according to the IPC&PLC&Profibus-DP field-bus scheme. The local layer realize the local data acquisition, control local instrument and execute machine. The middle control layer was constructed by a PLC Control Station and intelligent temperature controller, the former implement the basic logical function and the special control algorithm. The system manager and monitor layer which realize remote monitor and control by displaying technological flow and warming interface is consisted by an IPC. The system manager and monitor acquire production process data by communicating with PLC and intelligent temperature controller.
In system design, firing system of kiln is a multi-variant coupling non-linear system, which is the difficulty of system control. According to the autonomous and compensatory theory, the paper proposes the scheme which divides the system into temperature, air-natural gas ratio and tiny positave pressure loops. In the loop we use feedback control system. Considering the long delay, non-linear and time-variable characters of kiln, intelligent control arithmetic was introduced in temperature control loop. The FUZZY-PID parameter self-adaptive controller was designed to optimize the system control scheme.
In order to improve the veracity of design, and find the best parameters and structure, the advanced LSM is introduced in modeling for temperature control loop. The models were simulated in MATLAB with PID control and FUZZY control; the results show that the improved control method is better than PID control method in control veracity and robustness.
本文根据热处理炉的工艺流程和特点,在监控系统整体设计上采用工控机(IPC)+PLC+Profibus-DP现场总线的方案,将系统分为现场执行层、中间控制层和系统管理监控层。现场执行层主要完成现场数据的采集,现场仪表和执行机构的控制功能。中间控制层为PLC控制站和智能温控仪,PLC控制站主要完成基本的逻辑控制功能,实现特殊控制算法。系统管理与监控层由一台IPC组成,通过与PLC、智能温控仪通信来获取生产过程的数据,显示工艺流程、报警画面,实现远程监控。
在系统设计中,热处理炉温控系统作为一个多变量耦合的非线性系统,是控制的难点。通过对其特性进行分析,根据功能区分的原则,将温控系统分成燃烧、燃空比控制、炉膛压力三个回路进行控制,并在主要回路中采用反馈控制系统的方案。同时考虑到热处理炉属于大延迟、非线性时变对象,在温度控制回路中采用了智能控制算法,设计了参数自整定FUZZY-PID控制器,实现了系统控制方案的优化。
为了提高系统设计的准确性,寻找控制系统的最佳结构和参数,本文采用引入辅助变量的改进最小二乘法对温度控制回路建立了数学模型,并用MATLAB对建立的模型分别进行了PID控制方法和模糊控制方法的仿真。仿真结果比较表明,改进的设计方案具有较高控制精度和较好的鲁棒性。
The heat treatment kiln is widely used in industrial production. This paper gives a comprehensive research on kiln production process control system, and designs a set of intelligent monitor and distributed control system(DCS) in the the heat treatment kiln manufacturing process combined hardware with software.
According to the technical flow and characters of heat treatment kiln, the control system was divided into locale layer, middle control layer, and system management layer according to the IPC&PLC&Profibus-DP field-bus scheme. The local layer realize the local data acquisition, control local instrument and execute machine. The middle control layer was constructed by a PLC Control Station and intelligent temperature controller, the former implement the basic logical function and the special control algorithm. The system manager and monitor layer which realize remote monitor and control by displaying technological flow and warming interface is consisted by an IPC. The system manager and monitor acquire production process data by communicating with PLC and intelligent temperature controller.
In system design, firing system of kiln is a multi-variant coupling non-linear system, which is the difficulty of system control. According to the autonomous and compensatory theory, the paper proposes the scheme which divides the system into temperature, air-natural gas ratio and tiny positave pressure loops. In the loop we use feedback control system. Considering the long delay, non-linear and time-variable characters of kiln, intelligent control arithmetic was introduced in temperature control loop. The FUZZY-PID parameter self-adaptive controller was designed to optimize the system control scheme.
In order to improve the veracity of design, and find the best parameters and structure, the advanced LSM is introduced in modeling for temperature control loop. The models were simulated in MATLAB with PID control and FUZZY control; the results show that the improved control method is better than PID control method in control veracity and robustness.
引文
[1]许跃明,樊东黎著.热处理与可持续发展[J].金属热处理,2001.26(3)
[2]邬敏.金属材料热处理炉炉温模糊控制方法研究.吉林大学硕士学位论文,2006
[3]宋绍京著.温度控制系统技术研究[J]红外,2004.1:25-29
[4]廖芳芳,肖建.集散系统设计与应用.西南交通大学硕士研究生学位论文,2005
[5]汪璇炫,葛锁良.模糊PD控制在工业过程控制中的应用研究.合肥工业大学硕士学位论文,2005
[6]曹月东.模糊PID控制器分析及设计.中国科学院自动化研究所博士论文,2002
[7]全江楚,刘广钟.多台燃煤有机热载体炉供热DCS控制系统.上海海事大学工程硕士学位论文,2005
[8]秦家伟,戴汝平,谢军龙.DCS技术的多锅炉智能控制.华中科技大学硕士学位论文,2005
[9]郝万君,强文义.模糊建模与控制及其在电厂热工自动控制中的应用.哈尔滨工业大学博士学位论文,2006
[10]王立新.自适应模糊系统与控制.设计与稳定性分析.北京:国防工业出版社,1995
[11]李岩岩,任祖平.热处理过程控制小型集散系统的研究与实现.东南大学硕士学位论文,2003
[12]孟海龙,刘元法,曹同乐.步进式加热炉控制系统的设计.山东科技大学工程硕士论文,2004
[13]袁熙武,程耕国.加热炉燃烧系统的模糊控制研究.武汉科技大学硕士学位论文,2005
[14]付平妹.中板加热炉计算机智能控制系统[[J].电子与自动化,1998
[15]梁军.轧钢加热炉计算机集成控制系统的研究及实现[[J].钢铁,1998
[16]金笛,邵诚.热轧过程加热炉综合优化控制策略及控制方法研究.大连理工大学硕士学位论文,2005
[17]王玲,李胜玉.模糊神经网络控制技术在加热炉过程控制中的应用.节能技术,2002,20(4):14-16
[18]王耀南,付夏龙.模糊神经网络炉温自学习控制系统.冶金自动化,1998,22(2):31-37
[19]蔡自兴,陈海燕,魏世勇.智能控制工程研究的进展.控制工程,2003,10(1):1-6
[20]齐蓉,林辉.通用模糊控制器在PLC上的实现.工业仪表与自动化装置,NO.4,2003
[21]王辉,肖建,严殊.关于模糊系统辨识近年来的研究与发展.信息与控制,2004,33(4):445-450
[22]于浩洋,宋清昆,景方.基于MATLAB下的双模糊控制器的设计及仿真.黑龙江省自动化学会2002年学术年会论文集,2002:118-122
[23]宋清昆,于浩洋,李双全.一种新型的模糊控制器—双模糊控制器.黑龙江省自动化学会 2002年学术年会论文集,铁力,2002:114-117
[24]]Serge Guillaume.Designing Fuzzy Inference Systems from Data:An Interpretability-Oriented Review,IEEE Trans,on Fuzzy Systems,2001,9(3):426-443
[25]Chang X G,Wei L,Farrell J.A C-means clustering based fuzzy madeling method.The Ninth IEEE International Conference on Fuzzy System,San Antolio,IEEE Press,2000.937-940
[26]张平安,熊学健,李仁厚.基于拟非线形模糊模型的复杂系统模糊辨识.控制理论与应用,1998,15(2):286-290
[27]Yao J,Dash M,Tan S T,Liu H.Entropy-based fuzzy clustering and fuzzy modeling.Fuzzy sets and systems,2000,113:381-388
[28]Chen M S,Wang S W.Fuzzy clustering analysis for optimizing fuzzy membership functions.Fuzzy sets and systems,1999,103:239-254
[29]Xu J X,et al.Parallel structure and tuning of a fuzzy PID controller.Automatica,2000,36(4):673-684
[30]邵青,冯汝鹏.非线形系统模糊辨识的新方法.控制与决策,2001,6(1)
[31]H.J.Rong,N.Sundararajan,G.B.Huang,P.Saratchandran.Sequential Adaptive Fuzzy Inference System(SAFIS) for nonlinear system identification and prediction.Fuzzy Sets and Systems,2006,157
[32]Papadakis S E,Theocharis J B.A GA-based fuzzy modeling approach for generating TSK models.Fuzzy sets and systems,2002,131:121-152
[33]Huang Y P,Wang S F.Designing a fuzzy model by adaptive acroevolution genetic algorithms.Fuzzy sets and systems,2000,113:367-379
[34]Yun Li,Kiam Heong Ang,Gregory C.Y.Chong.PID Control System Analysis and Design Problems,Remedies,and Future Directions.IEEE Control Systems Magazine,2006,32-41
[35]马国华.组态软件的发展趋势与现状.清华大学出版社,2001
[36]King-view系列组态王6.52使用手册.北京亚控科技发展有限公司,2006
[37]]张汝森.热处理燃料炉的现状与展望.工业加热,2000(6):1-3
[38]]王鸣.一种模糊自整定PID参数控制器的设计与仿真.安徽机电学院学报,1999 14(2):23-40
[39]毛义梅,罗海福,张静.一种PID参数模糊自整定控制器的设计与仿真.自动化仪表,2001,16(3):36-38
[40]侯北平,卢佩,付连昆.自适应模糊PID控制器的设计及基于MATLAB的计算机仿真,天津轻工学院学报,2001,7(4):32-34
[41]黄晓宇.基于MATLAB的模糊自整定PID参数控制器计算机仿真.自动化与仪器仪表,2001,8(3):21-24
[42]Chiu S L.Fuzzy model identification based on cluster estimation.Jounal of Intelligent and Fuzzy Systems,1994,2(3):267-278.
[43]Wang L,Langari R.Complex systems modeling via fuzzy logic.IEEE Trans,Systems,Man and Cybernetics,1996,26(1):100-106.
[44]B.G.Hu,G.K.I.Mann,R.G.Gosine.A Systematic Study of Fuzzy PID Controllers-Function-based Evaluation Approach.Submitted to IEEE Transactions on Fuzzy Systems,1999
[2]邬敏.金属材料热处理炉炉温模糊控制方法研究.吉林大学硕士学位论文,2006
[3]宋绍京著.温度控制系统技术研究[J]红外,2004.1:25-29
[4]廖芳芳,肖建.集散系统设计与应用.西南交通大学硕士研究生学位论文,2005
[5]汪璇炫,葛锁良.模糊PD控制在工业过程控制中的应用研究.合肥工业大学硕士学位论文,2005
[6]曹月东.模糊PID控制器分析及设计.中国科学院自动化研究所博士论文,2002
[7]全江楚,刘广钟.多台燃煤有机热载体炉供热DCS控制系统.上海海事大学工程硕士学位论文,2005
[8]秦家伟,戴汝平,谢军龙.DCS技术的多锅炉智能控制.华中科技大学硕士学位论文,2005
[9]郝万君,强文义.模糊建模与控制及其在电厂热工自动控制中的应用.哈尔滨工业大学博士学位论文,2006
[10]王立新.自适应模糊系统与控制.设计与稳定性分析.北京:国防工业出版社,1995
[11]李岩岩,任祖平.热处理过程控制小型集散系统的研究与实现.东南大学硕士学位论文,2003
[12]孟海龙,刘元法,曹同乐.步进式加热炉控制系统的设计.山东科技大学工程硕士论文,2004
[13]袁熙武,程耕国.加热炉燃烧系统的模糊控制研究.武汉科技大学硕士学位论文,2005
[14]付平妹.中板加热炉计算机智能控制系统[[J].电子与自动化,1998
[15]梁军.轧钢加热炉计算机集成控制系统的研究及实现[[J].钢铁,1998
[16]金笛,邵诚.热轧过程加热炉综合优化控制策略及控制方法研究.大连理工大学硕士学位论文,2005
[17]王玲,李胜玉.模糊神经网络控制技术在加热炉过程控制中的应用.节能技术,2002,20(4):14-16
[18]王耀南,付夏龙.模糊神经网络炉温自学习控制系统.冶金自动化,1998,22(2):31-37
[19]蔡自兴,陈海燕,魏世勇.智能控制工程研究的进展.控制工程,2003,10(1):1-6
[20]齐蓉,林辉.通用模糊控制器在PLC上的实现.工业仪表与自动化装置,NO.4,2003
[21]王辉,肖建,严殊.关于模糊系统辨识近年来的研究与发展.信息与控制,2004,33(4):445-450
[22]于浩洋,宋清昆,景方.基于MATLAB下的双模糊控制器的设计及仿真.黑龙江省自动化学会2002年学术年会论文集,2002:118-122
[23]宋清昆,于浩洋,李双全.一种新型的模糊控制器—双模糊控制器.黑龙江省自动化学会 2002年学术年会论文集,铁力,2002:114-117
[24]]Serge Guillaume.Designing Fuzzy Inference Systems from Data:An Interpretability-Oriented Review,IEEE Trans,on Fuzzy Systems,2001,9(3):426-443
[25]Chang X G,Wei L,Farrell J.A C-means clustering based fuzzy madeling method.The Ninth IEEE International Conference on Fuzzy System,San Antolio,IEEE Press,2000.937-940
[26]张平安,熊学健,李仁厚.基于拟非线形模糊模型的复杂系统模糊辨识.控制理论与应用,1998,15(2):286-290
[27]Yao J,Dash M,Tan S T,Liu H.Entropy-based fuzzy clustering and fuzzy modeling.Fuzzy sets and systems,2000,113:381-388
[28]Chen M S,Wang S W.Fuzzy clustering analysis for optimizing fuzzy membership functions.Fuzzy sets and systems,1999,103:239-254
[29]Xu J X,et al.Parallel structure and tuning of a fuzzy PID controller.Automatica,2000,36(4):673-684
[30]邵青,冯汝鹏.非线形系统模糊辨识的新方法.控制与决策,2001,6(1)
[31]H.J.Rong,N.Sundararajan,G.B.Huang,P.Saratchandran.Sequential Adaptive Fuzzy Inference System(SAFIS) for nonlinear system identification and prediction.Fuzzy Sets and Systems,2006,157
[32]Papadakis S E,Theocharis J B.A GA-based fuzzy modeling approach for generating TSK models.Fuzzy sets and systems,2002,131:121-152
[33]Huang Y P,Wang S F.Designing a fuzzy model by adaptive acroevolution genetic algorithms.Fuzzy sets and systems,2000,113:367-379
[34]Yun Li,Kiam Heong Ang,Gregory C.Y.Chong.PID Control System Analysis and Design Problems,Remedies,and Future Directions.IEEE Control Systems Magazine,2006,32-41
[35]马国华.组态软件的发展趋势与现状.清华大学出版社,2001
[36]King-view系列组态王6.52使用手册.北京亚控科技发展有限公司,2006
[37]]张汝森.热处理燃料炉的现状与展望.工业加热,2000(6):1-3
[38]]王鸣.一种模糊自整定PID参数控制器的设计与仿真.安徽机电学院学报,1999 14(2):23-40
[39]毛义梅,罗海福,张静.一种PID参数模糊自整定控制器的设计与仿真.自动化仪表,2001,16(3):36-38
[40]侯北平,卢佩,付连昆.自适应模糊PID控制器的设计及基于MATLAB的计算机仿真,天津轻工学院学报,2001,7(4):32-34
[41]黄晓宇.基于MATLAB的模糊自整定PID参数控制器计算机仿真.自动化与仪器仪表,2001,8(3):21-24
[42]Chiu S L.Fuzzy model identification based on cluster estimation.Jounal of Intelligent and Fuzzy Systems,1994,2(3):267-278.
[43]Wang L,Langari R.Complex systems modeling via fuzzy logic.IEEE Trans,Systems,Man and Cybernetics,1996,26(1):100-106.
[44]B.G.Hu,G.K.I.Mann,R.G.Gosine.A Systematic Study of Fuzzy PID Controllers-Function-based Evaluation Approach.Submitted to IEEE Transactions on Fuzzy Systems,1999