基于WinCC和OPC的硫酸串酸多变量模型预测控制实现研究
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摘要
多变量模型预测控制在保证产品质量、提高产品产量、降低生产成本、减少环境污染等方面具有独特的优势,对企业提高经济效益,增强自身的竞争力都有极大的促进作用,已成为自动化领域研究的热点。
在铜冶炼过程中,转炉、艾萨炉、电炉会产生大量的烟气,由于烟气中含有大量的SO_2,如果直接排放,将会污染环境,而且还浪费了资源。为了保护环境和回收利用烟气中的SO_2资源,需要通过烟气制备硫酸工艺过程进行处理,一是可以获得重要的化工原料硫酸;二是可以净化尾气,实现达标排放,达到保护环境的目的。
云铜硫酸分厂利用铜冶炼中烟气制备硫酸,其工艺采用稀酸洗涤、半封闭净化、二转二吸流程。由于铜冶炼烟气波动较大,给硫酸生产过程的控制造成一定的难度。本论文针对硫酸生产过程中干吸串酸具有强耦合、大滞后、干扰多的特点,选用应用广泛的预测控制技术中的动态矩阵控制DMC(Dynamic MatrixControl)作为其控制算法。首先在深入分析DMC控制原理以及获得干吸串酸模型的基础上,开发了VC下的串酸过程DMC算法软件并进行了仿真研究,验证了DMC算法具有较好的控制效果;为了更好的将该算法应用于工程实际,结合过程控制领域中另一项新技术——OPC(OLE for Process Control)技术的优势,又开发了基于OPC技术的VC客户端多变量模型预测控制算法模块,并实现了与WinCC6.0应用软件之间的数据通信。
论文的研究具有较强的工程背景,所开发的应用软件人机交互友好,具有一定的实用性和推广价值。
Multi-variable Model Predictive Control has unique advantages in guaranteeing the production quality,improving the production quantity,reducing production cost, decreasing environment pollution etc.It can improve the enterprise's economy efficiency and strengthen enterprise's competition ability,which has become the issue in automation research field.
The converter,the AiSa stove and the electric stove will produce massive hazes, because the haze includes massive SO_2 in the copper metallurgical process.If it is directly discharged,it will not only pollute the environment,but also will waste the resources.In order to protect the environment and recycle the SO_2 resources from hazes,we need to deal with it through the metallurgical sulfuric acid technological process.Firstly,it can obtain the important industrial chemicals,sulfuric acid;Second, it can purify the metallurgical off-gas,reach the discharge standard and achieve the goal of protecting environment.
YunNan Copper sulfuric acid branch factory uses copper metallurgical off-gas to produce sulfuric acid.Its craft uses the diluted acid to wash,half seal purifies and the process of two transformation and two absorption.The control of sulfuric acid production is difficult because of the copper metallurgical off-gas changes strongly. The article selects the DMC(Dynamic Matrix Control),which is widely used in Predictive Control technology as the control algorithm in view of sulfuric acid-connecting system section have the characteristics of strongly coupling,big delay and many disturbs.
Firstly,on the basis of deeply analysis of the DMC control principle and obtaining the model of sulfuric acid-connecting system,The DMC algorithm software is developed with Visual C++,and the simulation research is finished,which testify DMC has good control result.In order to apply the algorithm in the actual program,it is also developed that Multivariable Model Predictive Control algorithm model realized the date communication with WinCC6.0,on the basis of the advantages of another new technology-OPC(OLE for Process Control)
The research of this article has the stronger project background and the human-machine interaction of application software is friendly,it is valuable in application and promotion.
在铜冶炼过程中,转炉、艾萨炉、电炉会产生大量的烟气,由于烟气中含有大量的SO_2,如果直接排放,将会污染环境,而且还浪费了资源。为了保护环境和回收利用烟气中的SO_2资源,需要通过烟气制备硫酸工艺过程进行处理,一是可以获得重要的化工原料硫酸;二是可以净化尾气,实现达标排放,达到保护环境的目的。
云铜硫酸分厂利用铜冶炼中烟气制备硫酸,其工艺采用稀酸洗涤、半封闭净化、二转二吸流程。由于铜冶炼烟气波动较大,给硫酸生产过程的控制造成一定的难度。本论文针对硫酸生产过程中干吸串酸具有强耦合、大滞后、干扰多的特点,选用应用广泛的预测控制技术中的动态矩阵控制DMC(Dynamic MatrixControl)作为其控制算法。首先在深入分析DMC控制原理以及获得干吸串酸模型的基础上,开发了VC下的串酸过程DMC算法软件并进行了仿真研究,验证了DMC算法具有较好的控制效果;为了更好的将该算法应用于工程实际,结合过程控制领域中另一项新技术——OPC(OLE for Process Control)技术的优势,又开发了基于OPC技术的VC客户端多变量模型预测控制算法模块,并实现了与WinCC6.0应用软件之间的数据通信。
论文的研究具有较强的工程背景,所开发的应用软件人机交互友好,具有一定的实用性和推广价值。
Multi-variable Model Predictive Control has unique advantages in guaranteeing the production quality,improving the production quantity,reducing production cost, decreasing environment pollution etc.It can improve the enterprise's economy efficiency and strengthen enterprise's competition ability,which has become the issue in automation research field.
The converter,the AiSa stove and the electric stove will produce massive hazes, because the haze includes massive SO_2 in the copper metallurgical process.If it is directly discharged,it will not only pollute the environment,but also will waste the resources.In order to protect the environment and recycle the SO_2 resources from hazes,we need to deal with it through the metallurgical sulfuric acid technological process.Firstly,it can obtain the important industrial chemicals,sulfuric acid;Second, it can purify the metallurgical off-gas,reach the discharge standard and achieve the goal of protecting environment.
YunNan Copper sulfuric acid branch factory uses copper metallurgical off-gas to produce sulfuric acid.Its craft uses the diluted acid to wash,half seal purifies and the process of two transformation and two absorption.The control of sulfuric acid production is difficult because of the copper metallurgical off-gas changes strongly. The article selects the DMC(Dynamic Matrix Control),which is widely used in Predictive Control technology as the control algorithm in view of sulfuric acid-connecting system section have the characteristics of strongly coupling,big delay and many disturbs.
Firstly,on the basis of deeply analysis of the DMC control principle and obtaining the model of sulfuric acid-connecting system,The DMC algorithm software is developed with Visual C++,and the simulation research is finished,which testify DMC has good control result.In order to apply the algorithm in the actual program,it is also developed that Multivariable Model Predictive Control algorithm model realized the date communication with WinCC6.0,on the basis of the advantages of another new technology-OPC(OLE for Process Control)
The research of this article has the stronger project background and the human-machine interaction of application software is friendly,it is valuable in application and promotion.
引文
[1]席裕庚.预测控制.国防工业出版社,1993.6
[2]舒迪前.预测控制系统及其应用.机械工业出版社,1996.3
[3]王树青等.先进控制技术及应用.化学工业出版社,2001.7
[4]董四禄.我国冶炼烟气制酸的现状及发展前景.硫酸工业,2005.1:55-56
[5]Morari。 Model predictive control past,present and future,Computers ＆ Chemical Engineering,1999(23):667-682
[6]j.Richalet。 Industrial application of model based predictive control,Automatica,1993,29:1251-1274
[7]Seung Cheol Jeong and PooGyeon Park。 Constrained MPC Algorithm for Uncertain Time-VaryingSystems With State-Delay,IEEE Transaction On Automation Control,2005,50(2):257-263
[8]Stephen Wright,Jim Rawlings,Matt Tenny。Optimization Problems in Model Predictive Control,Gabriele Pannocchia University of Wisconsin-Madison,2002,
[9]Dae Yyook Yang。 Model Predictive Control,Dept of Chemical and Biological Engineering of Korea University,2002
[10]孙优贤.工业过程控制技术.化学工业出版社,2006
[11]邵雪飞,一类计算机新型控制策略-预测控制的改进研究及仿真设计,1999.5
[12]金晓明,模型预测控制及其工业应用,化工自动化及仪表,1999.26(5)
[13]李言俊,张科.系统辨识理论及应用.国防工业出版社,2003.5
[14]李曼珍.工业过程对象的实用辨识.仪器仪表用户.2005.12(4)
[15]王修中,二阶加滞后连续模型的直接辨识,自动化学报,2001.27(5)
[16]朱豫才,过程控制的多变量系统辨识,国防科技大学出版社,2005.8
[17]Nilos.Drakos。An Overview of Industrial Model Predictive Control Technology.Computer Based Learning Unit.University of Leeds,1999
[18]Ashraf Al-Ghazzawi。 On-line Tuning Strategy for Model Predictive Controllers,Journal of Process Control,2001.(11):265-284
[19]Mark J.Willis & Ming T.Tham,Advanced Process Control,Chemical and process engineering,2001
[20]Magnus Akerblad and Anders Hansson,Efficient Solution of Second Order Cone Program For Model Predictive Control,15th IFAC Triennial World Congress,2002
[21]DMCplus-Dynamic matrix control software,Aspentech Company
[22]B.Wayne Bequett,Model Predictive Control,2000.9
[23]Seborg,D.A.A perspective on advanced strategies for process control.Modeling,Identification and Control,1994.15(3):179-189
[24]D.Q.Mayne et al.Constrained model predictive control:Stability and optimality.Automatica2000.36:789-814
[25]Lee J H,Yu ZH.Tuning of Model Predictive Controller for Robust Performance.Computer Chem Eng,1994,18(1):15-37
[26]闫志恒.过程控制系统实时预测控制软件开发与应用.上海交通大学.2003
[27]管善功.模型预测控制算法在应用中的研究和软件包的实现.华北电力大学.2006
[28]戴懿纯.动态矩阵预测控制软件.广西大学.2004.5
[29]闫志恒,李少远.基于PC机平台的预测控制系统仿真软件开发与实现.系统仿真学报.2002
[30]张宏军等.Visual C++6.0编程案例精解.电子工业出版社.2005.1
[31]金以慧,方崇智.过程控制.清华大学出版社1993.4:p22-24
[32]易继锴,侯媛彬.智能控制技术.北京工业大学出版社1999.9:p9
[33]濮强国.动态矩阵控制方法的仿真研究.苏州城建环保学院学报.2002
[34]陈荣保,李劲松.基于动态矩阵算法的液位控制系统.自动化仪表.2001
[35]孙进生,高炉热风炉燃烧CBR智能控制技术,冶金工业出版社2006.10
[36]西门子(中国)有限公司自动化与驱动集团.深入浅出西门子WinCC V6.北京航空航天大学出版社2004.11:p110-113
[37]姜捷李等.OPC规范简介(二).自动化仪表.2002.6.67-69
[38]孙德敏等.工业过程先进控制及优化软件产业.自动化博览.2003.2
[39]金以慧.生产过程的先进控制.化工自动化及仪表.1997.24(4)
[40]梁春燕,谢剑英.预测控制中的若干问题研究.自动化与仪器仪表.1999(4)
[41]席裕庚,耿晓军,陈虹.预测控制性能研究的新进展.控制理论与应用.Vol.17.No.4
[42]赵众,邹芳云,徐宁等.OPC客户端程序开发及其在集散控制系统中的应用.化工自动化及仪表,2007,34(3):42-46
[43]刘丽,王海文.基于OPCXML DA实现远程实时监控的研究及设计.化工自动化及仪表.2007,34(2):32-35
[2]舒迪前.预测控制系统及其应用.机械工业出版社,1996.3
[3]王树青等.先进控制技术及应用.化学工业出版社,2001.7
[4]董四禄.我国冶炼烟气制酸的现状及发展前景.硫酸工业,2005.1:55-56
[5]Morari。 Model predictive control past,present and future,Computers ＆ Chemical Engineering,1999(23):667-682
[6]j.Richalet。 Industrial application of model based predictive control,Automatica,1993,29:1251-1274
[7]Seung Cheol Jeong and PooGyeon Park。 Constrained MPC Algorithm for Uncertain Time-VaryingSystems With State-Delay,IEEE Transaction On Automation Control,2005,50(2):257-263
[8]Stephen Wright,Jim Rawlings,Matt Tenny。Optimization Problems in Model Predictive Control,Gabriele Pannocchia University of Wisconsin-Madison,2002,
[9]Dae Yyook Yang。 Model Predictive Control,Dept of Chemical and Biological Engineering of Korea University,2002
[10]孙优贤.工业过程控制技术.化学工业出版社,2006
[11]邵雪飞,一类计算机新型控制策略-预测控制的改进研究及仿真设计,1999.5
[12]金晓明,模型预测控制及其工业应用,化工自动化及仪表,1999.26(5)
[13]李言俊,张科.系统辨识理论及应用.国防工业出版社,2003.5
[14]李曼珍.工业过程对象的实用辨识.仪器仪表用户.2005.12(4)
[15]王修中,二阶加滞后连续模型的直接辨识,自动化学报,2001.27(5)
[16]朱豫才,过程控制的多变量系统辨识,国防科技大学出版社,2005.8
[17]Nilos.Drakos。An Overview of Industrial Model Predictive Control Technology.Computer Based Learning Unit.University of Leeds,1999
[18]Ashraf Al-Ghazzawi。 On-line Tuning Strategy for Model Predictive Controllers,Journal of Process Control,2001.(11):265-284
[19]Mark J.Willis & Ming T.Tham,Advanced Process Control,Chemical and process engineering,2001
[20]Magnus Akerblad and Anders Hansson,Efficient Solution of Second Order Cone Program For Model Predictive Control,15th IFAC Triennial World Congress,2002
[21]DMCplus-Dynamic matrix control software,Aspentech Company
[22]B.Wayne Bequett,Model Predictive Control,2000.9
[23]Seborg,D.A.A perspective on advanced strategies for process control.Modeling,Identification and Control,1994.15(3):179-189
[24]D.Q.Mayne et al.Constrained model predictive control:Stability and optimality.Automatica2000.36:789-814
[25]Lee J H,Yu ZH.Tuning of Model Predictive Controller for Robust Performance.Computer Chem Eng,1994,18(1):15-37
[26]闫志恒.过程控制系统实时预测控制软件开发与应用.上海交通大学.2003
[27]管善功.模型预测控制算法在应用中的研究和软件包的实现.华北电力大学.2006
[28]戴懿纯.动态矩阵预测控制软件.广西大学.2004.5
[29]闫志恒,李少远.基于PC机平台的预测控制系统仿真软件开发与实现.系统仿真学报.2002
[30]张宏军等.Visual C++6.0编程案例精解.电子工业出版社.2005.1
[31]金以慧,方崇智.过程控制.清华大学出版社1993.4:p22-24
[32]易继锴,侯媛彬.智能控制技术.北京工业大学出版社1999.9:p9
[33]濮强国.动态矩阵控制方法的仿真研究.苏州城建环保学院学报.2002
[34]陈荣保,李劲松.基于动态矩阵算法的液位控制系统.自动化仪表.2001
[35]孙进生,高炉热风炉燃烧CBR智能控制技术,冶金工业出版社2006.10
[36]西门子(中国)有限公司自动化与驱动集团.深入浅出西门子WinCC V6.北京航空航天大学出版社2004.11:p110-113
[37]姜捷李等.OPC规范简介(二).自动化仪表.2002.6.67-69
[38]孙德敏等.工业过程先进控制及优化软件产业.自动化博览.2003.2
[39]金以慧.生产过程的先进控制.化工自动化及仪表.1997.24(4)
[40]梁春燕,谢剑英.预测控制中的若干问题研究.自动化与仪器仪表.1999(4)
[41]席裕庚,耿晓军,陈虹.预测控制性能研究的新进展.控制理论与应用.Vol.17.No.4
[42]赵众,邹芳云,徐宁等.OPC客户端程序开发及其在集散控制系统中的应用.化工自动化及仪表,2007,34(3):42-46
[43]刘丽,王海文.基于OPCXML DA实现远程实时监控的研究及设计.化工自动化及仪表.2007,34(2):32-35
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