模糊控制在加氢脱硫催化反应器中的应用
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摘要
加热反应是化学实验中十分常见的化学反应之一。电加热炉结构简单、密封性能好,适用于各类化学反应场合,因此得到了广泛地应用。由于在加热过程中电加热炉的特性参数实时改变,应用一般的PID控制方法无法解决超调和滞后问题。本课题有关加氢脱硫催化反应温度控制的研究正是基于这种应用背景提出来的。
分析了所研究的电加热炉产生超调和滞后的原因,介绍了模糊控制系统的结构,对模糊控制原理中模糊子集、隶属函数、模糊语言以及推理规则进行了分析,并对几种常用的模糊逻辑系统的优缺点进行了比较。
针对催化反应对温度控制的要求和电加热炉的系统特性,研究了一种带多个调整因子的模糊控制方法。这种控制方法针对被控对象的不同状态,通过修改后的调整因子的值来改变各个输入量在计算模糊输出时所占的权重,实现了模糊控制的智能化,解决电加热炉在加热过程中出现的超调问题,改善了电加热炉在升温过程中的升温速度剧烈波动的问题。
介绍PLC(可编程逻辑控制器)的性能指标和编程语言,将PLC作为系统的主控制器,通过编程进行模糊控制,并采用指针实现PLC的多段程序升温控制。采用Visual Studio.NET在计算机上开发监控软件,使用MODBUS TCP协议与PLC进行以太网通讯。监控软件分为数据处理模块和参数设置模块,数据处理模块实现对采集数据的储存和显示,参数设置模块对温度控制参数以及监控系统参数进行设置。
通过实验验证,采用带多个调整因子的模糊控制算法能有效地解决电加热炉温度控制中的温度超调和升温速度问题,达到预期的控温效果。
In chemical experiments, Heating reactions are quite common chemical reactions In chemical experiments. As Electric heating furnace is applicable to all kinds of chemical reaction occasions because of its simple structure and good sealing performance, it had been widely applied. However, furnace characteristic parameters are real-time changed in the process of heating, it is highly difficult to solve overshoot and lag issues with the application of general PID control method. The topic about temperature control in the hydrodesulfurization catalytic reaction is based on this application background.
Reason of overshoot and lag electric heating furnace generated is exactly analyzed, and structure of fuzzy control system is introduced. Moreover, advantages and disadvantages of several common fuzzy control logical systems are well compared by analyzing the fuzzy subsets, membership functions, fuzzy language and reasoning rules in fuzzy control principles.
For temperature control-requirements in catalytic reactions and system characteristics of electric heating furnace, it presented a fuzzy control method with multiple adjusting factors, which can alter input weight in the-process of fuzzy output calculation according with changed adjusting factor. Therefore, implemented intelligence of fuzzy control, figured out overshoot issues in heating process, and reduced dramatic fluctuation of heating rate in temperature rise process of electric heating furnace.
Introduced and programmable of PLC (programmable logical controller), used PLC as main controller of system to realize fuzzy control, and used Pointers of PLC to implement multisegment programming temperature rising control.
Developed monitor software on the computer using Visual studio.net, and achieved PLC Ethernet communication adopting MODBUS TCP protocol. This software is divided into data processing module which implements for store and display of collected data and parameters Setting module for the parameters about temperature control and system monitor related.
It has been verified effectively that algorithm of fuzzy control with adjusting factors could not only solve overshoot and heating rate issues in the process of temperature control of electric heating furnace, but also attain the prospective temperature control effects.
分析了所研究的电加热炉产生超调和滞后的原因,介绍了模糊控制系统的结构,对模糊控制原理中模糊子集、隶属函数、模糊语言以及推理规则进行了分析,并对几种常用的模糊逻辑系统的优缺点进行了比较。
针对催化反应对温度控制的要求和电加热炉的系统特性,研究了一种带多个调整因子的模糊控制方法。这种控制方法针对被控对象的不同状态,通过修改后的调整因子的值来改变各个输入量在计算模糊输出时所占的权重,实现了模糊控制的智能化,解决电加热炉在加热过程中出现的超调问题,改善了电加热炉在升温过程中的升温速度剧烈波动的问题。
介绍PLC(可编程逻辑控制器)的性能指标和编程语言,将PLC作为系统的主控制器,通过编程进行模糊控制,并采用指针实现PLC的多段程序升温控制。采用Visual Studio.NET在计算机上开发监控软件,使用MODBUS TCP协议与PLC进行以太网通讯。监控软件分为数据处理模块和参数设置模块,数据处理模块实现对采集数据的储存和显示,参数设置模块对温度控制参数以及监控系统参数进行设置。
通过实验验证,采用带多个调整因子的模糊控制算法能有效地解决电加热炉温度控制中的温度超调和升温速度问题,达到预期的控温效果。
In chemical experiments, Heating reactions are quite common chemical reactions In chemical experiments. As Electric heating furnace is applicable to all kinds of chemical reaction occasions because of its simple structure and good sealing performance, it had been widely applied. However, furnace characteristic parameters are real-time changed in the process of heating, it is highly difficult to solve overshoot and lag issues with the application of general PID control method. The topic about temperature control in the hydrodesulfurization catalytic reaction is based on this application background.
Reason of overshoot and lag electric heating furnace generated is exactly analyzed, and structure of fuzzy control system is introduced. Moreover, advantages and disadvantages of several common fuzzy control logical systems are well compared by analyzing the fuzzy subsets, membership functions, fuzzy language and reasoning rules in fuzzy control principles.
For temperature control-requirements in catalytic reactions and system characteristics of electric heating furnace, it presented a fuzzy control method with multiple adjusting factors, which can alter input weight in the-process of fuzzy output calculation according with changed adjusting factor. Therefore, implemented intelligence of fuzzy control, figured out overshoot issues in heating process, and reduced dramatic fluctuation of heating rate in temperature rise process of electric heating furnace.
Introduced and programmable of PLC (programmable logical controller), used PLC as main controller of system to realize fuzzy control, and used Pointers of PLC to implement multisegment programming temperature rising control.
Developed monitor software on the computer using Visual studio.net, and achieved PLC Ethernet communication adopting MODBUS TCP protocol. This software is divided into data processing module which implements for store and display of collected data and parameters Setting module for the parameters about temperature control and system monitor related.
It has been verified effectively that algorithm of fuzzy control with adjusting factors could not only solve overshoot and heating rate issues in the process of temperature control of electric heating furnace, but also attain the prospective temperature control effects.
引文
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[2]李翔,王安杰,孙仲超等.全硅MCM-41担载的Ni-W催化剂上二苯并噻吩加氢脱硫反应动力学研究[J].石油学报.2003,19,(4)：1-7.
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[5]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)：347-355.
[6]Xu Y, Hollerbach J M, Ma D. A nonlinear PD controller for force and contact transient control[J], IEEE Control System Magazine,1995,15(1):15-21.
[7]Brian Armstrong, Bruce AWade. Nonlinear PID control with partial state knowledge: Damping without derivatives[J].Int J Robotics Res,2000,19(8):715-731.
[8]Haissing C. Adaptive fuzzy temperature control for hydronic heating system [J]. IEEE Control Systems-Magazine,2000,20(2):39-48.
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[12]舒迪前,刘宏才,吴保亮等.智能自适应控制及其在轧辊退火炉上的应用智能自适应控制及其在轧辊退火炉上的应用[J].自动化学报,1991,17(2)：207-214.
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[15]李少远,蔡文剑.工业过程辨识与控制[M].北京：化学工业出版社,2005.
[16]文定都.一类纯滞后系统Fuzzy-Dahlin控制策略研究[J].工业仪表与自动化装置,2007,3(4)：3-5.
[17]傅燕,周琼,杨建刚.改进型Smith预估控制系统的仿真[J].计算机仿真.1998,15(4)：39-41
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[22]张培建,吴建国.大纯滞后系统的研究与应用[J].东南大学学报,2004,34(9)：271-275.
[23]Brian Armstrong, Bruce A Wade. Nonlinear PID control with partial state knowledge: Damping without derivatives[J]. Int J Robotics Res,2000,19(8):715-731.
[24]高岩,龚至豪,黄鸿.锅炉燃烧系统的仿人智能控制[J].北京理工大学学报.2002,22(3)：315-317.
[25]Li Ping, Jin Fu-jiang. Adaptive Fuzzy Control for Unknown Nonlinear Systems with Perturbed Dead-zone Inputs[J]. ACTA AUTOMATICA SINICA,2010,36(4):573-579.
[26]Zadeh L A. Fuzzy sets[J]. Information and control,1965,8:338-353.
[27]Zadeh L A. Outline of a new approach to the analysis of complex systems and decision Processes[J]. IEEE Trans on Systems Man and Cybern,1973,3(1):28-44.
[28]Mahdani E. H. Application of fuzzy algorithms for simple dynamic plant[C]. Proc. Inst. Elect.Eng,1974,121(12):1585-1588.
[29]俞金寿,蒋慰孙.过程控制工程[M].北京：电子工业出版社,2007.
[30]项国波.时滞系统优化控制[M].北京：中国电力出版社,2008.
[31]韩京清.从PID技术到“自抗扰控制”技术[J].控制工程,2002,9(3)：13-18.
[32]R. R. Yager et al, Analysis of flexible structured fuzzy logic controllers[J],IEEE Trans. Systems, Man and Cybernetics,1994,24(7):1035-1043.
[33]李士勇,夏承光.模糊控制和智能控制理论与应用[M].哈尔滨：哈尔滨工业大学出版社,1990.
[34]董猛,会国涛,刘耕成.一类时滞随机分布参数系统的模糊控制[J].东北大学学报(自然科学版),2010,31(3)：317-329.
[35]Wang liang, yen J. Extractiong fuzzy rules for system modeling using a hybrid of genetic algorrithms and Kalman filter[J].Fuzzy Sets and Systems,1999,101 (3): 353-362.
[36]刘向杰,柴天佑.动力锅炉燃烧系统的模糊控制策略[J].自动化学报.1998,24(4).
[37]宋云霞.大时滞过程控制策略与方法的研究(华南理工大学博士学位论文).广州：华南理工大学,2002.
[38]欧进萍,张吉礼.作用模糊子集推理方法的研究与应用[J].模糊系统与数学,2000,14(3)：58-65.
[39]张吉礼,赵天怡,刘辉.基于多维ANFIS的T-S模糊控制规则聚类获取方法[J].大连理工大学学报,2010,50(4)：580-585.
[40]陈永攀,卢振,张吉礼等.散热器试验台送风系统规则自提取模糊控制试验[J].天津大学学报,2010,43(1)：43-49.
[41]Takagi T, Sugeno M. Fuzzy indentification of systems and its applications to modeling and control[J]. IEEE Trans. Syst, Man, Cybern.1985,15(1):116-132.
[42]舒迪前,刘立.多变量自校正调节器及其在电加热炉上的应用[J].自动化学报,1985,1 1(1)：21-29.
[43]张生,李翔,王安杰.有机含氮化合物对深度加氢脱硫反应的影响[J].工业催化2005,13(11)：12-17.
[44]陆玲霞,汪雄海.给予模糊控制的电磁水热系统的研究[J].浙江大学学报(工学版),2008,42(4)：598-601.
[45]段后利,李力,李志恒等.城市交叉口自学习模糊控制策略[J].清华大学学报(自然科学版),2010,50(5)：709-713.
[46]尤煜敏.基于自校正控制的大滞后控制过程研究[D].大连：大连理工大学,2008.
[47]CHEN G. Conventional and fuzzy PID controllers:An overiew[J].International Journal of Intelligent Control and Systems,1984,12(2):123-1-40.
[148]张永辉,邵诚,崔波.铝粉雾化炉铝业温度模糊-PID复合控制[J].大连理工大学学报,2006,46(4)：572-575.
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[2]李翔,王安杰,孙仲超等.全硅MCM-41担载的Ni-W催化剂上二苯并噻吩加氢脱硫反应动力学研究[J].石油学报.2003,19,(4)：1-7.
[3]陶永华,尹怡欣,葛芦生.新型PID控制系统及其应用[M]、.北京：机械工业出版社,1998.
[4]刘金琨.先进PID控制MATLAB仿真[M].北京：电子工业出版社,2004.
[5]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)：347-355.
[6]Xu Y, Hollerbach J M, Ma D. A nonlinear PD controller for force and contact transient control[J], IEEE Control System Magazine,1995,15(1):15-21.
[7]Brian Armstrong, Bruce AWade. Nonlinear PID control with partial state knowledge: Damping without derivatives[J].Int J Robotics Res,2000,19(8):715-731.
[8]Haissing C. Adaptive fuzzy temperature control for hydronic heating system [J]. IEEE Control Systems-Magazine,2000,20(2):39-48.
[9]周峰,李翔,王安杰等.CoNiMo/MCM-41催化的二苯并噻吩加氢脱硫反应[J].石油学报(石油化工),2008,24(5)：491-495.
[10]王顺晃,舒迪前.智能控制系统及其应用[M].北京：机械工业出版社, 2005.
[11]潘峰,韩如成.时变大时滞系统的控制方法综述[J].仪器仪表学报,2002,23(3)：789-791.
[12]舒迪前,刘宏才,吴保亮等.智能自适应控制及其在轧辊退火炉上的应用智能自适应控制及其在轧辊退火炉上的应用[J].自动化学报,1991,17(2)：207-214.
[13]韩京清,张文革.大时滞系统的自抗扰控制[J].控制与决策,1999,14(4)：354-358.
[14]周黎英,赵国树.模糊PID控制算法在恒速升温系统中的应用[J].仪器仪表学报.2008,29(2)：405-409.
[15]李少远,蔡文剑.工业过程辨识与控制[M].北京：化学工业出版社,2005.
[16]文定都.一类纯滞后系统Fuzzy-Dahlin控制策略研究[J].工业仪表与自动化装置,2007,3(4)：3-5.
[17]傅燕,周琼,杨建刚.改进型Smith预估控制系统的仿真[J].计算机仿真.1998,15(4)：39-41
[18]李清泉.系统辨识与自适应控制[M].北京：科学出版社,1990.
[19]丁永生,应浩,邵世煌.模糊逼近理论的现状与展望[J].信息与控制.2002,29(2)：157-163.
[20]王光远,欧进萍,汪培庄.动态模糊集[J].模糊系统与数学.1988,2(1)：1-8.
[21]周其鉴.仿人智能控制器[J].中国仪器仪表.1993,2：5-9.
[22]张培建,吴建国.大纯滞后系统的研究与应用[J].东南大学学报,2004,34(9)：271-275.
[23]Brian Armstrong, Bruce A Wade. Nonlinear PID control with partial state knowledge: Damping without derivatives[J]. Int J Robotics Res,2000,19(8):715-731.
[24]高岩,龚至豪,黄鸿.锅炉燃烧系统的仿人智能控制[J].北京理工大学学报.2002,22(3)：315-317.
[25]Li Ping, Jin Fu-jiang. Adaptive Fuzzy Control for Unknown Nonlinear Systems with Perturbed Dead-zone Inputs[J]. ACTA AUTOMATICA SINICA,2010,36(4):573-579.
[26]Zadeh L A. Fuzzy sets[J]. Information and control,1965,8:338-353.
[27]Zadeh L A. Outline of a new approach to the analysis of complex systems and decision Processes[J]. IEEE Trans on Systems Man and Cybern,1973,3(1):28-44.
[28]Mahdani E. H. Application of fuzzy algorithms for simple dynamic plant[C]. Proc. Inst. Elect.Eng,1974,121(12):1585-1588.
[29]俞金寿,蒋慰孙.过程控制工程[M].北京：电子工业出版社,2007.
[30]项国波.时滞系统优化控制[M].北京：中国电力出版社,2008.
[31]韩京清.从PID技术到“自抗扰控制”技术[J].控制工程,2002,9(3)：13-18.
[32]R. R. Yager et al, Analysis of flexible structured fuzzy logic controllers[J],IEEE Trans. Systems, Man and Cybernetics,1994,24(7):1035-1043.
[33]李士勇,夏承光.模糊控制和智能控制理论与应用[M].哈尔滨：哈尔滨工业大学出版社,1990.
[34]董猛,会国涛,刘耕成.一类时滞随机分布参数系统的模糊控制[J].东北大学学报(自然科学版),2010,31(3)：317-329.
[35]Wang liang, yen J. Extractiong fuzzy rules for system modeling using a hybrid of genetic algorrithms and Kalman filter[J].Fuzzy Sets and Systems,1999,101 (3): 353-362.
[36]刘向杰,柴天佑.动力锅炉燃烧系统的模糊控制策略[J].自动化学报.1998,24(4).
[37]宋云霞.大时滞过程控制策略与方法的研究(华南理工大学博士学位论文).广州：华南理工大学,2002.
[38]欧进萍,张吉礼.作用模糊子集推理方法的研究与应用[J].模糊系统与数学,2000,14(3)：58-65.
[39]张吉礼,赵天怡,刘辉.基于多维ANFIS的T-S模糊控制规则聚类获取方法[J].大连理工大学学报,2010,50(4)：580-585.
[40]陈永攀,卢振,张吉礼等.散热器试验台送风系统规则自提取模糊控制试验[J].天津大学学报,2010,43(1)：43-49.
[41]Takagi T, Sugeno M. Fuzzy indentification of systems and its applications to modeling and control[J]. IEEE Trans. Syst, Man, Cybern.1985,15(1):116-132.
[42]舒迪前,刘立.多变量自校正调节器及其在电加热炉上的应用[J].自动化学报,1985,1 1(1)：21-29.
[43]张生,李翔,王安杰.有机含氮化合物对深度加氢脱硫反应的影响[J].工业催化2005,13(11)：12-17.
[44]陆玲霞,汪雄海.给予模糊控制的电磁水热系统的研究[J].浙江大学学报(工学版),2008,42(4)：598-601.
[45]段后利,李力,李志恒等.城市交叉口自学习模糊控制策略[J].清华大学学报(自然科学版),2010,50(5)：709-713.
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