糖厂蒸发工段的建模和控制
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摘要
蒸发工段是制糖工艺的关键步骤。对蒸发工段的有效控制,首先保证了末效出口糖浆浓度的稳定,满足煮糖工段对工艺的要求;同时减少了能量的消耗,具有显著的经济效益。因而研究蒸发工段多效蒸发系统的建模与控制对于具有重要意义。
在了解了蒸发工艺流程和多效蒸发原理的基础之上,根据多效蒸发系统强干扰、非线性、多约束等特点,利用BP人工神经网络建立了多效蒸发系统二效压力和末效出口糖浆浓度之间的人工神经网络模型。系统仿真实验显示,建立的模型具有较好的逼近能力,能够较好的反映系统末效出口糖浆浓度的输出特性。
论文的另一部分工作是介绍了预测控制算法,对非线性预测控制在多效蒸发系统中的应用进行了深入的研究和探讨,提出了以BP神经网络建立预测模型、遗传算法进行滚动优化的预测控制算法。以所建的神经网络模型作为对象对多效蒸发系统实施非线性预测控制仿真。仿真结果表明,控制效果较好,可以达到控制要求。
The evaporator station is a key process step in the cane sugar mill. Its robust control is essential to guarantee the output syrup concentration as close as possible to the desired values to feed to the crystallization process and optimize the energy used. Therefore, modeling and control of the evaporating process is of the highest importance in the sugar industry.
On the basis of comprehension of the evaporating process flow and principle of multiple-effect evaporation, according to the following plant features: strong disturbances, great nonlinearity, many constrains and so on, The error BP(BackProragation)neural network is used to establish a model and describe the complex relationship among the juice steam pressure of the second stage and the syrup brix leaving the multiple-effect evaporator. The simulation result proves the validity of the model which has strong ability to describe the multiple-effect evaporation and reveal the performance of the syrup brix leaving the multiple-effect evaporator.
The predictive control algorithm is introduced in another part of the dissertation, and analyze application of nonlinear MPC in cane sugar multiple-effect evaporation, then a MPC algorithm which based on BP neural network model and genetic algorithm optimization is discussed. A simulation has been taken to the multiple-effect evaporation by means of nonlinear MPC algorithms. From simulation result, it receives good effect and reaches the requirement of control.
在了解了蒸发工艺流程和多效蒸发原理的基础之上,根据多效蒸发系统强干扰、非线性、多约束等特点,利用BP人工神经网络建立了多效蒸发系统二效压力和末效出口糖浆浓度之间的人工神经网络模型。系统仿真实验显示,建立的模型具有较好的逼近能力,能够较好的反映系统末效出口糖浆浓度的输出特性。
论文的另一部分工作是介绍了预测控制算法,对非线性预测控制在多效蒸发系统中的应用进行了深入的研究和探讨,提出了以BP神经网络建立预测模型、遗传算法进行滚动优化的预测控制算法。以所建的神经网络模型作为对象对多效蒸发系统实施非线性预测控制仿真。仿真结果表明,控制效果较好,可以达到控制要求。
The evaporator station is a key process step in the cane sugar mill. Its robust control is essential to guarantee the output syrup concentration as close as possible to the desired values to feed to the crystallization process and optimize the energy used. Therefore, modeling and control of the evaporating process is of the highest importance in the sugar industry.
On the basis of comprehension of the evaporating process flow and principle of multiple-effect evaporation, according to the following plant features: strong disturbances, great nonlinearity, many constrains and so on, The error BP(BackProragation)neural network is used to establish a model and describe the complex relationship among the juice steam pressure of the second stage and the syrup brix leaving the multiple-effect evaporator. The simulation result proves the validity of the model which has strong ability to describe the multiple-effect evaporation and reveal the performance of the syrup brix leaving the multiple-effect evaporator.
The predictive control algorithm is introduced in another part of the dissertation, and analyze application of nonlinear MPC in cane sugar multiple-effect evaporation, then a MPC algorithm which based on BP neural network model and genetic algorithm optimization is discussed. A simulation has been taken to the multiple-effect evaporation by means of nonlinear MPC algorithms. From simulation result, it receives good effect and reaches the requirement of control.
引文
[1]郭晓洁,包桂莲.糖厂蒸发系统分析型模型建立和计算机程序设计[J].中国甜菜糖业,1998,47(10):30-40
[2]周巍,胡绍川.多效蒸发系统各效能耗分配的分析计算[J].应用能源技术,1995
[3]王培进,周作伸.多效蒸发系统的数学描述及优化目标函数分析[J].化学工程,1997,25(2):33-38
[4]谭学富,王红心,秦忠顺.多效蒸发过程模拟的严格Broyden法计算[J].沈阳化工学院学报,1998,12(3):204-209
[5]李德虎,李培宁,琚定一.五效蒸发模拟与优化研究(Ⅰ)-模拟研究[J].化学工程,1995,23(6):29-33
[6]施有铸,陈宗海,鲍元律.多效蒸发器的仿真建模[J].计算机仿真,1996,13(4):25-29
[7]阮奇,陈文波,黄诗煌.复杂并流多效蒸发系统的数学模型与矩阵解法[J].中国工程科学,2001,3(4):36-41
[8]陈文波,陈华新,施得志,阮奇.并流多效蒸发系统的计算机辅助计算[J].福州大学学报,2001,29(3):99-104
[9]徐建良,陈晓祥.复杂并流多效蒸发系统的模拟[J].华东理工大学学报,2004,30(1):23-30
[10]姜莹,许中侠.基于Guass-Seidel迭代法的多效并流蒸发过程的模拟以及优化方法[J].化工技术与开发,2005,34(3):44-47
[11]李德虎.多效蒸发过程模拟与优化回顾[J].化工装备技书,1993,14(6):35-38
[12]Hisham T.E1-Dessouky,H.M.Ettouney.Multiple-effect evaporation desalination systems:thermal analysis[J].Desalination 125(1999):259-276
[13]Hisham T.E1-Dessouky,Hisham M.Ettouney,Faisal Mandani.Performance of parallel feed multiple effect evaporation system for seawater desalination[J].Applied Thermal Engineering 20(2000):1679-1706
[14]K.Urbaniec.The evolution of evaporator stations in the beet-sugar industry[J].Journal of Food Engineering 61(2004):505-508
[15]Durmus Kaya,H.Ibrahim Sarae.Mathematical modeling of multiple-effect evaporators and energy economy[J].Energy10(2006):1-7
[16]吴刚,陈宗海,薛美盛,张志刚,孙德敏.建模与先进控制在多效蒸发器节能中的应用[J].中国科学技术大学学报,1999,29(1):30-37
[17]陈金水,王慧,孙优贤.黑液蒸发出浓液浓度的控制实践-基于前馈+反馈的预测控制算法[J].China Pulp&Paper,1998
[18]S.Lissane Elhaq,F.Giri,H.Unbehauen.Modelling,identification and control of sugar evaporation--theoretical design and experimental evaluation[J].Control Engineering Practice 7(1999):931-942
[19]C.Cadet,Y.Toure,G.Gilles,J.P.Chabriat.Knowledge modeling and nonlinear predictive control of evaporators in cane sugar production plants[J].Journal of Food Engineering 40(1999):59-70
[20]M.Benne,B.Grondin-Perez,J-P.Chabriat,P.Herve.Artificial neural networks for modeling and predictive control of an Industrial evaporation process[J].Journal of Food Engineering 46(2000):227-234
[21]陈维钧,许斯欣.甘蔗制糖原理与技术[M].中国轻工业出版社,2001
[22]韩力群.人工神经网络理论、设计及应用[M].北京:北京化学工业出版社,2002
[23]王永骥,涂健.神经元网络控制[M],北京:机械工业出版社,1998
[24]赵林明.多层前向人工神经网络[M].黄河水利出版社,1999
[25]张吉礼.模糊-神经网络控制原理与工程应用[M].哈尔滨工业大学出版社,2004
[26]李国勇.智能控制及其MATLAB实现[M].北京:电子工业出版社,2005
[27]飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社,2005
[28]梁海葵,何小阳.基于ANN的糖厂蒸发工段的建模[J].湖南工业大学学报,2007,21(6):80-82
[29]席裕庚.预测控制[M].北京:国防工业出版社,1993
[30]Richalet J,Rault A,Tesud L,and Papon J.Model Predictive heuristic control:Applications to industrial Processes[J].Automatica,978,14(5):413-428
[31]Rouhani R,Mehra,R K.Model Algorithmic Control(MAC);Basic Theoretical Properties[J].Automatica,.1982,18(4):401-414
[32]Culter C R,Ramaker B L.Dynamic Matrix Control--A Computer Control Algorithm[M].Pro c.Join Automatic Control Conference,San Francisco,1980
[33]舒迪前.预测控制系统及其应用[M].北京:机械工业出版社,1996
[34]褚静.智能预测控制及其应用[M].浙江大学出版社,2002
[35]李少远.复杂系统的模糊预测控制及其应用[M].科学出版社,2003
[36]胡国龙,孙优贤.预测控制进展及其应用研究[J].电力系统及其自动化学报,2003,15(1):109-114
[37]黄湘云,朱学峰.预测控制的研究现状与展望[J].石油化工自动化,2005,2:27-37
[38]李嗣福,许自富,李亚秦.Winner型非线性系统的La-RBF组合模型预测控制[J].信息与控制,2001,30(4):305-309
[39]许强,许晓明,张卫东.基于Volterra模型的非线性系统预测控制[J].控制与决策,2000,15(3):339-344
[40]黄道平,朱学峰,周其节.基于广义Hammerstein模型的多变量非线性预测控制[J].暨南大学学报(自然科学版),1998,19(1):13-19
[41]Danielle Dougherty,Doug Cooper.A practical multiple model adaptive strategy for single-loop MPC[J].Control Engineering Practice 11(2003):141-159
[42]张智焕,王树青.基于多模糊模型的非线性预测控制[J].信息与控制,2001,30(7):673-375
[43]王寅,荣冈,王树青.基于T-S模糊模型的非线性预测控制策略[J].控制理论与应用,2002,19(4):599-603
[44]张日东,李平,陈江林.基于神经网络的非线性系统约束预测控制[J].工业仪表与自动化装置,2004,1:3-6
[45]蔡宁,李胜,赵英凯.基于径向基函数神经网络的非线性系统预测控制[J].石油化工自动化,2002年5月:31-33
[46]刘金琨.先进PID控制Matalb仿真[M].电子工业出版社.2005
[47]周明,孙树栋.遗传算法原理及应用[M].国防工业出版社.1999
[2]周巍,胡绍川.多效蒸发系统各效能耗分配的分析计算[J].应用能源技术,1995
[3]王培进,周作伸.多效蒸发系统的数学描述及优化目标函数分析[J].化学工程,1997,25(2):33-38
[4]谭学富,王红心,秦忠顺.多效蒸发过程模拟的严格Broyden法计算[J].沈阳化工学院学报,1998,12(3):204-209
[5]李德虎,李培宁,琚定一.五效蒸发模拟与优化研究(Ⅰ)-模拟研究[J].化学工程,1995,23(6):29-33
[6]施有铸,陈宗海,鲍元律.多效蒸发器的仿真建模[J].计算机仿真,1996,13(4):25-29
[7]阮奇,陈文波,黄诗煌.复杂并流多效蒸发系统的数学模型与矩阵解法[J].中国工程科学,2001,3(4):36-41
[8]陈文波,陈华新,施得志,阮奇.并流多效蒸发系统的计算机辅助计算[J].福州大学学报,2001,29(3):99-104
[9]徐建良,陈晓祥.复杂并流多效蒸发系统的模拟[J].华东理工大学学报,2004,30(1):23-30
[10]姜莹,许中侠.基于Guass-Seidel迭代法的多效并流蒸发过程的模拟以及优化方法[J].化工技术与开发,2005,34(3):44-47
[11]李德虎.多效蒸发过程模拟与优化回顾[J].化工装备技书,1993,14(6):35-38
[12]Hisham T.E1-Dessouky,H.M.Ettouney.Multiple-effect evaporation desalination systems:thermal analysis[J].Desalination 125(1999):259-276
[13]Hisham T.E1-Dessouky,Hisham M.Ettouney,Faisal Mandani.Performance of parallel feed multiple effect evaporation system for seawater desalination[J].Applied Thermal Engineering 20(2000):1679-1706
[14]K.Urbaniec.The evolution of evaporator stations in the beet-sugar industry[J].Journal of Food Engineering 61(2004):505-508
[15]Durmus Kaya,H.Ibrahim Sarae.Mathematical modeling of multiple-effect evaporators and energy economy[J].Energy10(2006):1-7
[16]吴刚,陈宗海,薛美盛,张志刚,孙德敏.建模与先进控制在多效蒸发器节能中的应用[J].中国科学技术大学学报,1999,29(1):30-37
[17]陈金水,王慧,孙优贤.黑液蒸发出浓液浓度的控制实践-基于前馈+反馈的预测控制算法[J].China Pulp&Paper,1998
[18]S.Lissane Elhaq,F.Giri,H.Unbehauen.Modelling,identification and control of sugar evaporation--theoretical design and experimental evaluation[J].Control Engineering Practice 7(1999):931-942
[19]C.Cadet,Y.Toure,G.Gilles,J.P.Chabriat.Knowledge modeling and nonlinear predictive control of evaporators in cane sugar production plants[J].Journal of Food Engineering 40(1999):59-70
[20]M.Benne,B.Grondin-Perez,J-P.Chabriat,P.Herve.Artificial neural networks for modeling and predictive control of an Industrial evaporation process[J].Journal of Food Engineering 46(2000):227-234
[21]陈维钧,许斯欣.甘蔗制糖原理与技术[M].中国轻工业出版社,2001
[22]韩力群.人工神经网络理论、设计及应用[M].北京:北京化学工业出版社,2002
[23]王永骥,涂健.神经元网络控制[M],北京:机械工业出版社,1998
[24]赵林明.多层前向人工神经网络[M].黄河水利出版社,1999
[25]张吉礼.模糊-神经网络控制原理与工程应用[M].哈尔滨工业大学出版社,2004
[26]李国勇.智能控制及其MATLAB实现[M].北京:电子工业出版社,2005
[27]飞思科技产品研发中心.神经网络理论与MATLAB7实现[M].北京:电子工业出版社,2005
[28]梁海葵,何小阳.基于ANN的糖厂蒸发工段的建模[J].湖南工业大学学报,2007,21(6):80-82
[29]席裕庚.预测控制[M].北京:国防工业出版社,1993
[30]Richalet J,Rault A,Tesud L,and Papon J.Model Predictive heuristic control:Applications to industrial Processes[J].Automatica,978,14(5):413-428
[31]Rouhani R,Mehra,R K.Model Algorithmic Control(MAC);Basic Theoretical Properties[J].Automatica,.1982,18(4):401-414
[32]Culter C R,Ramaker B L.Dynamic Matrix Control--A Computer Control Algorithm[M].Pro c.Join Automatic Control Conference,San Francisco,1980
[33]舒迪前.预测控制系统及其应用[M].北京:机械工业出版社,1996
[34]褚静.智能预测控制及其应用[M].浙江大学出版社,2002
[35]李少远.复杂系统的模糊预测控制及其应用[M].科学出版社,2003
[36]胡国龙,孙优贤.预测控制进展及其应用研究[J].电力系统及其自动化学报,2003,15(1):109-114
[37]黄湘云,朱学峰.预测控制的研究现状与展望[J].石油化工自动化,2005,2:27-37
[38]李嗣福,许自富,李亚秦.Winner型非线性系统的La-RBF组合模型预测控制[J].信息与控制,2001,30(4):305-309
[39]许强,许晓明,张卫东.基于Volterra模型的非线性系统预测控制[J].控制与决策,2000,15(3):339-344
[40]黄道平,朱学峰,周其节.基于广义Hammerstein模型的多变量非线性预测控制[J].暨南大学学报(自然科学版),1998,19(1):13-19
[41]Danielle Dougherty,Doug Cooper.A practical multiple model adaptive strategy for single-loop MPC[J].Control Engineering Practice 11(2003):141-159
[42]张智焕,王树青.基于多模糊模型的非线性预测控制[J].信息与控制,2001,30(7):673-375
[43]王寅,荣冈,王树青.基于T-S模糊模型的非线性预测控制策略[J].控制理论与应用,2002,19(4):599-603
[44]张日东,李平,陈江林.基于神经网络的非线性系统约束预测控制[J].工业仪表与自动化装置,2004,1:3-6
[45]蔡宁,李胜,赵英凯.基于径向基函数神经网络的非线性系统预测控制[J].石油化工自动化,2002年5月:31-33
[46]刘金琨.先进PID控制Matalb仿真[M].电子工业出版社.2005
[47]周明,孙树栋.遗传算法原理及应用[M].国防工业出版社.1999
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