基于预测模糊PID的氯乙烯聚合釜温控制研究
|
摘要
石油化工产业是国民经济的支柱性产业,化工产品中的聚氯乙烯(PVC)更是世界上产量及消费量最大的塑料产品之一。聚氯乙烯工业生产中,聚合反应占有重要地位,反应温度、容器压力、介质流量、流速均对聚合反应存在影响,其中对产品品质影响最大的是聚合反应的温度。因此对氯乙烯聚合过程的反应温度进行精确控制十分重要。
由于聚合反应机理较为复杂,过程存在强烈非线性、大惯性、大迟滞等特性,模型参数是不确定的,依赖于受控系统精确数学模型的经典控制策略无法获得理想的控制效果。所以寻求一种有效的控制策略以提高PVC聚合反应釜温控制精度是有必要的。
预测控制与模糊控制均对受控对象模型精度要求较低,预测控制具有鲁棒性强,可消除系统静态误差的特点,而模糊控制则在线调节能力强,实时性较好,可增强系统的抗扰性能。这样在PVC聚合釜热量系统中的夹套冷却环节上,结合预测控制和模糊控制的优点,设计一种预测模糊PID控制器,以进一步提高温度控制效果。
本文在简述了PVC生产过程相关工艺流程,深入分析聚合反应釜动态特性的基础上,结合预测控制及模糊控制技术,提出了一种相应控制算法,并设计了预测模糊PID控制器,理论和仿真研究表明:此控制策略具有超调量小、快速性好等优点,是提高聚合釜温度控制效果的一种有效方法。
Petrochemical industry is a leading industry of our national economics, as a kind of chemical products, polyvinyl chloride (PVC) is the largest production and consumption of plastic product in the world. PVC polymerization plays a very important role in industrial production, the reaction temperature、container pressure、medium flow、medium velocity all have effects on the polymerization reaction, in which the greatest influence on product quality is the temperature. Therefore, control precisely to temperature of PVC polymerization is very essential.
The polymerization reaction’s mechanism is very complex, there is strong nonlinearity, large inertia and delay and other characteristics in this process, model parameters are time-varying, depending on the accurate mathematical model of the controlled object-one kind of traditional control methods can not achieve satisfactoring control effect. So, seeking an efficient control method to enhance the effection of polymerization's temperature control is necessary.
Model predictive control and fuzzy control are all less precision to the controlled object model, MPC have some characteristices such as strong robustness, can eliminate the system static error, at the same time the fuzzy control have strong online adjustment, real-time well, can enhance the system anti-jamming capability. So in the link of the polymerization reactor’s jacket cooling system, combined with predictive control and fuzzy control technology, design a predictive fuzzy controller to further enhance the control effect.
This paper outlines the process of PVC production and related processes, based on in-depth analysis of polymerization dynamics, combined with Model Predictive Control and the fuzzy control technology, presents a corresponding control algorithm, and design a predictive fuzzy PID controller, theoretical analysis and simulation results shows: this control strategy has small overshoot、response rapidly, it is a effective method to improve the effection of temperature control of polyvinyl chloride reactor.
由于聚合反应机理较为复杂,过程存在强烈非线性、大惯性、大迟滞等特性,模型参数是不确定的,依赖于受控系统精确数学模型的经典控制策略无法获得理想的控制效果。所以寻求一种有效的控制策略以提高PVC聚合反应釜温控制精度是有必要的。
预测控制与模糊控制均对受控对象模型精度要求较低,预测控制具有鲁棒性强,可消除系统静态误差的特点,而模糊控制则在线调节能力强,实时性较好,可增强系统的抗扰性能。这样在PVC聚合釜热量系统中的夹套冷却环节上,结合预测控制和模糊控制的优点,设计一种预测模糊PID控制器,以进一步提高温度控制效果。
本文在简述了PVC生产过程相关工艺流程,深入分析聚合反应釜动态特性的基础上,结合预测控制及模糊控制技术,提出了一种相应控制算法,并设计了预测模糊PID控制器,理论和仿真研究表明:此控制策略具有超调量小、快速性好等优点,是提高聚合釜温度控制效果的一种有效方法。
Petrochemical industry is a leading industry of our national economics, as a kind of chemical products, polyvinyl chloride (PVC) is the largest production and consumption of plastic product in the world. PVC polymerization plays a very important role in industrial production, the reaction temperature、container pressure、medium flow、medium velocity all have effects on the polymerization reaction, in which the greatest influence on product quality is the temperature. Therefore, control precisely to temperature of PVC polymerization is very essential.
The polymerization reaction’s mechanism is very complex, there is strong nonlinearity, large inertia and delay and other characteristics in this process, model parameters are time-varying, depending on the accurate mathematical model of the controlled object-one kind of traditional control methods can not achieve satisfactoring control effect. So, seeking an efficient control method to enhance the effection of polymerization's temperature control is necessary.
Model predictive control and fuzzy control are all less precision to the controlled object model, MPC have some characteristices such as strong robustness, can eliminate the system static error, at the same time the fuzzy control have strong online adjustment, real-time well, can enhance the system anti-jamming capability. So in the link of the polymerization reactor’s jacket cooling system, combined with predictive control and fuzzy control technology, design a predictive fuzzy controller to further enhance the control effect.
This paper outlines the process of PVC production and related processes, based on in-depth analysis of polymerization dynamics, combined with Model Predictive Control and the fuzzy control technology, presents a corresponding control algorithm, and design a predictive fuzzy PID controller, theoretical analysis and simulation results shows: this control strategy has small overshoot、response rapidly, it is a effective method to improve the effection of temperature control of polyvinyl chloride reactor.
引文
[1]曹伟.基于迭代学习控制的PVC反应釜温度控制的鲁棒性研究[D].哈尔滨:哈尔滨工程大学硕士论文. 2009:1-5
[2]张晓军,张二为.智能控制系统发展综述及其应用[J].有色冶金设计与研究. 2001,27(1):8-11
[3]董克捷.我国PVC(聚氯乙烯)产业国际竞争力分析与评价[D].北京:首都经济贸易大学硕士论文. 2008:9-10
[4]杨惠娣.我国聚氯乙烯行业现状与发展趋势[J].塑料助剂. 2008,68(2):2-6
[5]朱星宇.聚氯乙烯:行业发展面临多重考验[N].中国化工报. 2008-1-12(2)
[6]张博.间歇反应釜变论域模糊控制系统的设计与实现[D].大连理工大学硕士论文. 2008:1-2
[7]杨巧玲,张海萍,刘恒胜.氯乙烯聚合反应过程的智能优化控制[J].化工自动化及仪表.2007,34(2):66-68
[8]周哲民,汤光华. PVC聚合釜温度自适应控制[J].工业控制计算机, 2010,23(4):22-24
[9]王燕芳,宋辉. DCS的发展对未来工业控制技术的影响[J].微计算机信息,2006,22(9):108-110
[10]潘祖仁.氯乙烯悬浮聚合动力学数学模型[J].浙江化工. 1979:1-6
[11] Bindlish, Rawlings, J.B. Target linearization and model predictive control of polymerization processes[J]. AIChE Journal. 2003:2885
[12]滕少龙.间歇反应釜先进控制系统的设计与实现[D].大连:大连理工大学硕士学位论文. 2006:3-8
[13] Zwe-Lee Gaing. A Particle Swarm Optimization Approach for Optimum Design of PID Controller in AVR System[J]. IEEE TRANSACTIONS ON ENERGY CONVERSION. 2003,19(2):384-387
[14]王蕊,苗宝增,李晓惠.基于FUZZY-PID双模控制的聚合釜温控系统[J].微计算机信息. 2007,23(5):46-48
[15]张文丽,刘洪对.预测模糊控制在聚合反应釜温控系统中的实现方法[J].工业控制计算机. 2007,20(2):43-44
[16]高异,刘军,杨延西.基于模糊遗传优化支持向量机的系统辨识研究[J].西安理工大学学报. 2006,22(1):49-54
[17]王凯,孙建中.工业聚合反应装置[M].北京:中国石化出版社,1997
[18] Miura N, Hashimoto. J Chem Eng J pn[J]. 1998:630-632
[19] Abonyi J, Szeifert F. Takagi-Sugeno fuzzy control of batch Polymerization Reactors[C]. IEEE International Conference on Intelligent Systems. 1997:250-253
[20] J.C.B. Gonzaga, L.A.C Meleiro, C. Kiang. ANN-based soft-sensor for real-time process monitoring and control of an industrial polymerization process[J]. Computers & Chemical Engineering. 2009,33(1):44-48
[21] Clarke, Mac Gregor J F. Ind Eng Chem Res. 1998:3660-3665
[22] Altinten, Ayla Karakurt, Sevtap Erdogan. Application of self-tuning PID control with genetic algorithm to a semi-batch polystyrene reactor[J]. Indian Journal of Chemical Technology. 2010,17(5):356-359
[23] Fen Wu. LMI-based robust model predictive control and its application to an industrial CSTR problem[J]. Journal of Process Control. 2001,11(6):650-658
[24]李国勇.智能控制及其MATLAB实现[M].北京:电子工业出版社,2005:285-286
[25]张浩然,韩正之,李昌刚.基于支持向量机的非线性模型预测控制[J].系统工程与电子技术. 2003:330-335
[26]丁惜瀛,崔紫薇,王凤翔.间歇式反应釜的温度预测控制[J].沈阳工业大学学报. 2007,29(6):716-720
[27]张泉灵,王树青.化学反应器温度跟踪预测函数控制的研究及应用[J].控制理论与应用. 2001,11(8):559-565
[28] Qiu-Xia Chen, Li Yu. A delay-dependent robust fuzzy MPC approach for nonlinear CSTR[J]. The Canadian Journal of Chemical Engineering. 2010,88(3):426-430
[29]楚焱芳,张瑞华.模糊控制理论概述[J].科技信息. 2009,(20):161-162
[30]乔杰,李曼珍,王开辉.模糊自整定PID控制在聚合反应中的研究[J].技术与方法. 2010,(1):67-69
[31] Niu Yixia, Song Jijiang. Temperature Controller of Heating Furnace of Crude Oil Based on Fuzzy Control and Expert System[J]. International Symposium on Test Automation and Instrumentation. 2006:698
[32]李永彪,孙正贵,赵青杰.间歇聚丙烯生产的智能控制方案[J].工业仪表与自动化装置. 2002:16-25
[33]李想,关明礼,李浚圣.工业过程控制系统基本理论及其发展过程[C].仪器仪表学报. 2008,29(4):22-24
[34]李国勇.智能控制及其MATLAB实现[M].北京:电子工业出版社,2005
[35]戴航,慕德俊.网络化工业控制系统的研究进展[J].测控技术.2008,27(1):1-3
[36]张仰森.人工智能原理与应用[M].北京:高等教育出版社,2004
[37] Fang Xibang, Chen Wuwei. Fuzzy Control Technology and The Application to Vehicle Semi Active Suspension[J]. Chinese Journal of Mechanical Engineering. 1999(3):2-5
[38]匡宇国,李小英.基于模糊PID预估控制的溶氧浓度优化控制系统[J].机电工程. 2007,8:56-59
[39]王俊,雷勇等.模糊预测控制在时滞系统中的应用[J].控制理论与应用. 2007,26(3):4-7
[40]聂云峰,高飞等.模糊预测控制在热电厂锅炉燃烧系统中的应用[J].自动化技术与应用. 2008,27(2):19-21
[41]聂林涛. PVC聚合反应器及其控制系统动态仿真[D].北京:北京化工大学硕士论文. 2007:23~30
[42] Alan D. Schmidt, W.Harmon Ray. The dynamic behavior of continuous polymerization reactors—Isothermal solution polymerization in a CSTR[J]. Chemical Engineering Science. 1981,36(8):1401-1410
[43] Lotfi A. Zadeh. Fuzzy sets as a basis for a theory of possibility[J]. Fuzzy Sets and Systems. 1998,100(1):10-32
[44] Xiao-Jun,MaZeng-Qi,SunYan-Yan. Analysis and design of fuzzy controller and fuzzy observer[J]. IEEE Computational Intelligence Society. 1998,6(1):42-50
[45] M. K. Passino,S. Yurkovich. Fuzzy Control[M].北京:清华大学出版社,2001:79-82
[46] Abid S. Fnaiech F,Najim M.A. Fast Feedforward Training Algorithm Using a Modified Form of the Standard Back propagation Algorithm[J].IEEE Trans.Newral Net.2001:424-430.
[47]严鸿瑞,马礼举.基于模糊神经网络智能预测模型的设计与实现[J].现代电子技术.2008:84-88
[48] Kiam Heong Ang, Yun Li. PID control system analysis,design and technology[J]. Signal Processing & Analysis. 2005,13(3):560-565
[49] A.Hoshino, K.Shinozaki, T.Mihara. Demonstration of the improved PID method for the accurate temperature control of ADRs[J]. Nuclear Instruments and Methods in Physics . 2006,559(2):663-665
[50] A.Hoshino, K.Shinozaki, T.Mihara. Improved PID Method of Temperature Control for Adiabatic Demagnetization Refrigerators[J]. Nuclear Instruments and Methodsin Physics. 2006,558(2):536-541
[51] Grey, J. P. A comparision of PID control algorithms[J]. Control Engineering. 1987, 34(3):102~105
[52] Astrom, K. J, Lund Univ. Toward Intelligent Control[J]. IEEE Control System Magazine. 1989:9(3):61-64
[53] Hagglund T. PID Controller:Theory,Design and tuning. Research Triangle Park[J]. Instrument Sciety of America. 1995
[54]王伟,张晶涛. PID参数先进整定方法综述[J].自动化学报. 2000,26(3):348-351
[55]杜玉晓,曹卫华等.煤气加热炉分布式智能优化控制系统[J].小型微机计算机系统. 2005:1647-165
[56]柴天佑,王永富.自适应模糊控制理论的研究综述[J].控制工程. 2006,13(3):193-198
[57] Haralambos Sarimveis, George Bafas. Fuzzy model predictive control of non-linear processes using genetic algorithms[J]. Fuzzy Sets and Systems. 2003,139(1):60-78
[2]张晓军,张二为.智能控制系统发展综述及其应用[J].有色冶金设计与研究. 2001,27(1):8-11
[3]董克捷.我国PVC(聚氯乙烯)产业国际竞争力分析与评价[D].北京:首都经济贸易大学硕士论文. 2008:9-10
[4]杨惠娣.我国聚氯乙烯行业现状与发展趋势[J].塑料助剂. 2008,68(2):2-6
[5]朱星宇.聚氯乙烯:行业发展面临多重考验[N].中国化工报. 2008-1-12(2)
[6]张博.间歇反应釜变论域模糊控制系统的设计与实现[D].大连理工大学硕士论文. 2008:1-2
[7]杨巧玲,张海萍,刘恒胜.氯乙烯聚合反应过程的智能优化控制[J].化工自动化及仪表.2007,34(2):66-68
[8]周哲民,汤光华. PVC聚合釜温度自适应控制[J].工业控制计算机, 2010,23(4):22-24
[9]王燕芳,宋辉. DCS的发展对未来工业控制技术的影响[J].微计算机信息,2006,22(9):108-110
[10]潘祖仁.氯乙烯悬浮聚合动力学数学模型[J].浙江化工. 1979:1-6
[11] Bindlish, Rawlings, J.B. Target linearization and model predictive control of polymerization processes[J]. AIChE Journal. 2003:2885
[12]滕少龙.间歇反应釜先进控制系统的设计与实现[D].大连:大连理工大学硕士学位论文. 2006:3-8
[13] Zwe-Lee Gaing. A Particle Swarm Optimization Approach for Optimum Design of PID Controller in AVR System[J]. IEEE TRANSACTIONS ON ENERGY CONVERSION. 2003,19(2):384-387
[14]王蕊,苗宝增,李晓惠.基于FUZZY-PID双模控制的聚合釜温控系统[J].微计算机信息. 2007,23(5):46-48
[15]张文丽,刘洪对.预测模糊控制在聚合反应釜温控系统中的实现方法[J].工业控制计算机. 2007,20(2):43-44
[16]高异,刘军,杨延西.基于模糊遗传优化支持向量机的系统辨识研究[J].西安理工大学学报. 2006,22(1):49-54
[17]王凯,孙建中.工业聚合反应装置[M].北京:中国石化出版社,1997
[18] Miura N, Hashimoto. J Chem Eng J pn[J]. 1998:630-632
[19] Abonyi J, Szeifert F. Takagi-Sugeno fuzzy control of batch Polymerization Reactors[C]. IEEE International Conference on Intelligent Systems. 1997:250-253
[20] J.C.B. Gonzaga, L.A.C Meleiro, C. Kiang. ANN-based soft-sensor for real-time process monitoring and control of an industrial polymerization process[J]. Computers & Chemical Engineering. 2009,33(1):44-48
[21] Clarke, Mac Gregor J F. Ind Eng Chem Res. 1998:3660-3665
[22] Altinten, Ayla Karakurt, Sevtap Erdogan. Application of self-tuning PID control with genetic algorithm to a semi-batch polystyrene reactor[J]. Indian Journal of Chemical Technology. 2010,17(5):356-359
[23] Fen Wu. LMI-based robust model predictive control and its application to an industrial CSTR problem[J]. Journal of Process Control. 2001,11(6):650-658
[24]李国勇.智能控制及其MATLAB实现[M].北京:电子工业出版社,2005:285-286
[25]张浩然,韩正之,李昌刚.基于支持向量机的非线性模型预测控制[J].系统工程与电子技术. 2003:330-335
[26]丁惜瀛,崔紫薇,王凤翔.间歇式反应釜的温度预测控制[J].沈阳工业大学学报. 2007,29(6):716-720
[27]张泉灵,王树青.化学反应器温度跟踪预测函数控制的研究及应用[J].控制理论与应用. 2001,11(8):559-565
[28] Qiu-Xia Chen, Li Yu. A delay-dependent robust fuzzy MPC approach for nonlinear CSTR[J]. The Canadian Journal of Chemical Engineering. 2010,88(3):426-430
[29]楚焱芳,张瑞华.模糊控制理论概述[J].科技信息. 2009,(20):161-162
[30]乔杰,李曼珍,王开辉.模糊自整定PID控制在聚合反应中的研究[J].技术与方法. 2010,(1):67-69
[31] Niu Yixia, Song Jijiang. Temperature Controller of Heating Furnace of Crude Oil Based on Fuzzy Control and Expert System[J]. International Symposium on Test Automation and Instrumentation. 2006:698
[32]李永彪,孙正贵,赵青杰.间歇聚丙烯生产的智能控制方案[J].工业仪表与自动化装置. 2002:16-25
[33]李想,关明礼,李浚圣.工业过程控制系统基本理论及其发展过程[C].仪器仪表学报. 2008,29(4):22-24
[34]李国勇.智能控制及其MATLAB实现[M].北京:电子工业出版社,2005
[35]戴航,慕德俊.网络化工业控制系统的研究进展[J].测控技术.2008,27(1):1-3
[36]张仰森.人工智能原理与应用[M].北京:高等教育出版社,2004
[37] Fang Xibang, Chen Wuwei. Fuzzy Control Technology and The Application to Vehicle Semi Active Suspension[J]. Chinese Journal of Mechanical Engineering. 1999(3):2-5
[38]匡宇国,李小英.基于模糊PID预估控制的溶氧浓度优化控制系统[J].机电工程. 2007,8:56-59
[39]王俊,雷勇等.模糊预测控制在时滞系统中的应用[J].控制理论与应用. 2007,26(3):4-7
[40]聂云峰,高飞等.模糊预测控制在热电厂锅炉燃烧系统中的应用[J].自动化技术与应用. 2008,27(2):19-21
[41]聂林涛. PVC聚合反应器及其控制系统动态仿真[D].北京:北京化工大学硕士论文. 2007:23~30
[42] Alan D. Schmidt, W.Harmon Ray. The dynamic behavior of continuous polymerization reactors—Isothermal solution polymerization in a CSTR[J]. Chemical Engineering Science. 1981,36(8):1401-1410
[43] Lotfi A. Zadeh. Fuzzy sets as a basis for a theory of possibility[J]. Fuzzy Sets and Systems. 1998,100(1):10-32
[44] Xiao-Jun,MaZeng-Qi,SunYan-Yan. Analysis and design of fuzzy controller and fuzzy observer[J]. IEEE Computational Intelligence Society. 1998,6(1):42-50
[45] M. K. Passino,S. Yurkovich. Fuzzy Control[M].北京:清华大学出版社,2001:79-82
[46] Abid S. Fnaiech F,Najim M.A. Fast Feedforward Training Algorithm Using a Modified Form of the Standard Back propagation Algorithm[J].IEEE Trans.Newral Net.2001:424-430.
[47]严鸿瑞,马礼举.基于模糊神经网络智能预测模型的设计与实现[J].现代电子技术.2008:84-88
[48] Kiam Heong Ang, Yun Li. PID control system analysis,design and technology[J]. Signal Processing & Analysis. 2005,13(3):560-565
[49] A.Hoshino, K.Shinozaki, T.Mihara. Demonstration of the improved PID method for the accurate temperature control of ADRs[J]. Nuclear Instruments and Methods in Physics . 2006,559(2):663-665
[50] A.Hoshino, K.Shinozaki, T.Mihara. Improved PID Method of Temperature Control for Adiabatic Demagnetization Refrigerators[J]. Nuclear Instruments and Methodsin Physics. 2006,558(2):536-541
[51] Grey, J. P. A comparision of PID control algorithms[J]. Control Engineering. 1987, 34(3):102~105
[52] Astrom, K. J, Lund Univ. Toward Intelligent Control[J]. IEEE Control System Magazine. 1989:9(3):61-64
[53] Hagglund T. PID Controller:Theory,Design and tuning. Research Triangle Park[J]. Instrument Sciety of America. 1995
[54]王伟,张晶涛. PID参数先进整定方法综述[J].自动化学报. 2000,26(3):348-351
[55]杜玉晓,曹卫华等.煤气加热炉分布式智能优化控制系统[J].小型微机计算机系统. 2005:1647-165
[56]柴天佑,王永富.自适应模糊控制理论的研究综述[J].控制工程. 2006,13(3):193-198
[57] Haralambos Sarimveis, George Bafas. Fuzzy model predictive control of non-linear processes using genetic algorithms[J]. Fuzzy Sets and Systems. 2003,139(1):60-78