推钢式型钢燃气加热炉燃烧控制策略的研究
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摘要
加热炉不仅是冶金行业的重要热工设备,而且也是耗能大户,能耗占到钢铁工业总能耗的25%。加热炉控制技术直接影响带钢产品的质量、能源消耗和轧机寿命。在钢铁冶金行业竞争日趋激烈的今天,实现加热炉的优化控制对钢铁企业意义重大。
加热炉的生产目的是满足轧制要求的钢坯温度分布,并实现钢坯表面氧化烧损最少、低的燃料消耗和环境污染。由于加热炉燃烧过程受随机干扰较多,具有非线性、大惯性、强耦合等特点,无法建立被控制对象的精确数学模型,因此采用传统的控制方法难以达到理想的控制效果,只能依靠操作人员凭经验控制底层回路设定值,当工况发生变化时往往使工艺指标实际值偏离目标值范围,造成产品质量下降,能耗增加。定量反馈理论是目前鲁棒控制领域中具有较强工程实用价值的一种设计方法,不需知道被控制对象的精确数学模型。针对以上情况,将定量反馈理论和模糊控制技术应用到加热炉控制中,就加燃气热炉控制中的温度-燃烧串级控制方式展开研究。具体来说,本文主要做了以下工作:首先,对加热炉系统进行深入研究,分析了加热炉的燃烧机理,用炉温-燃烧串级控制方式实现温度的自动控制。对炉温-燃烧串级控制中的主回路温度控制,应用实验法建立加热炉温度特性模型,用最小二乘法对模型参数进行辨识,根据辨识所得模型应用定量反馈理论进行温度控制器设计,在用模糊控制技术对控制器进行改进,实现参数的在线自调整,提高系统的适应性。其次,对现有加热炉燃烧控制策略中的双交叉限幅模型控制响应慢问题,研究设计了改进型变偏置双交叉限幅模型,在提高系统响应性能同时兼顾经济性。在分析了燃烧效率与空燃比关系后,针对炉内最佳空燃比随燃气热值和炉内工况变化的问题,设计了基于炉温变化、烟道残氧量并配合热值仪修正的空然比寻优模糊控制器,提高了燃烧效率。最后,对控制系统进行了仿真和性能分析,结果表明,所设计的控制器对加热炉工况变化有较强的鲁棒性,系统的响应性能和经济性更优。
论文对加热炉系统特性进行了深入的分析,建立了加热炉温度-燃烧串级控制系统,特别是对燃烧控制中空燃比的寻优设计和双交叉限幅模型的改进,不仅在学术研究方有较大的参考价值,还是具有一定的工程应用价值。
The reheating furnace is not only one of most important equipment of the steel mill, but also a large energy consumer on steel rolling line, and its consumption occupies about 25 percent of the energy consumption of the steel industry. Reheating furnace control technology directly affects the quality of rolled steel products energy consumption and mill life. Executing the optimal control of the reheating furnace is significant for iron and steel.
The purpose of reheat furnace production is to acquire the slab temperature distribution rolling required, and achieve the fewest stock scale loss, energy consumption and environment pollution. Because the furnace combustion process is affected by random disturbances more and it’s of nonlinearity, great inertia and coupling, so it is difficult to establish an accurate mode of controlled object, and achieve the ideal result by traditional control methods, which depend on the experience of the personnel operator to control the set values of lower level control loop. When the boundary conations change, which usually makes the technical specification actual values deviate the scope of target, and result decline in product quality, energy consumption increases. Quantitative feedback theory is a fashionable robust control theory rapidly developed in recent years, which has the advantage of engineering practicability, which don not need to know the precise mathematical model of controlled object. For the above, the quantitative feedback theory and fuzzy control technology are applied to reheating furnace control, and make research on these key problems including, temperature control, combustion control and optimizing ration of air to fuel. Specifically, this paper includes the main work as follows: First of all, this thesis has a profound research on combustion mechanism of reheating furnace, and using temperature combustion cascade control methods to control temperature automatically. Proposing establish furnace temperature model by experimental models, the least square method on the model parameters identification. According to the identification, a temperature controller is designed temperature design based on QFT. Meanwhile, using fuzzy control technology to improve the controller’s performance, and achieve online parameters self-tuning to improve the adaptability of the system. Second, we improve double cross limiting model slow response problems. After analyzing the relationship between combustion efficiency and air-fuel ratio, according to the problem of the best air/fuel excurses with fuel calorific value and changes in furnace conditions, optimization of air/fuel ratio's fuzzy controller assorting with the feed forward of the calorimeter based on temperature change and oxygen content of furnace flue. Combustion efficiency got improved. Finally, the control system simulation and performance analysis show that designed controller is robust on the furnace operating conditions change, system performance become well both in response and economy.
Based on the deep analysis of the reheating furnace characteristic, the reheating furnace temperature combustion control system has been designed, especially the optimizing design of Air/Fuel ratio and the improving of double-cross limit control model has great reference value both in academic research and practical applications in engineering.
加热炉的生产目的是满足轧制要求的钢坯温度分布,并实现钢坯表面氧化烧损最少、低的燃料消耗和环境污染。由于加热炉燃烧过程受随机干扰较多,具有非线性、大惯性、强耦合等特点,无法建立被控制对象的精确数学模型,因此采用传统的控制方法难以达到理想的控制效果,只能依靠操作人员凭经验控制底层回路设定值,当工况发生变化时往往使工艺指标实际值偏离目标值范围,造成产品质量下降,能耗增加。定量反馈理论是目前鲁棒控制领域中具有较强工程实用价值的一种设计方法,不需知道被控制对象的精确数学模型。针对以上情况,将定量反馈理论和模糊控制技术应用到加热炉控制中,就加燃气热炉控制中的温度-燃烧串级控制方式展开研究。具体来说,本文主要做了以下工作:首先,对加热炉系统进行深入研究,分析了加热炉的燃烧机理,用炉温-燃烧串级控制方式实现温度的自动控制。对炉温-燃烧串级控制中的主回路温度控制,应用实验法建立加热炉温度特性模型,用最小二乘法对模型参数进行辨识,根据辨识所得模型应用定量反馈理论进行温度控制器设计,在用模糊控制技术对控制器进行改进,实现参数的在线自调整,提高系统的适应性。其次,对现有加热炉燃烧控制策略中的双交叉限幅模型控制响应慢问题,研究设计了改进型变偏置双交叉限幅模型,在提高系统响应性能同时兼顾经济性。在分析了燃烧效率与空燃比关系后,针对炉内最佳空燃比随燃气热值和炉内工况变化的问题,设计了基于炉温变化、烟道残氧量并配合热值仪修正的空然比寻优模糊控制器,提高了燃烧效率。最后,对控制系统进行了仿真和性能分析,结果表明,所设计的控制器对加热炉工况变化有较强的鲁棒性,系统的响应性能和经济性更优。
论文对加热炉系统特性进行了深入的分析,建立了加热炉温度-燃烧串级控制系统,特别是对燃烧控制中空燃比的寻优设计和双交叉限幅模型的改进,不仅在学术研究方有较大的参考价值,还是具有一定的工程应用价值。
The reheating furnace is not only one of most important equipment of the steel mill, but also a large energy consumer on steel rolling line, and its consumption occupies about 25 percent of the energy consumption of the steel industry. Reheating furnace control technology directly affects the quality of rolled steel products energy consumption and mill life. Executing the optimal control of the reheating furnace is significant for iron and steel.
The purpose of reheat furnace production is to acquire the slab temperature distribution rolling required, and achieve the fewest stock scale loss, energy consumption and environment pollution. Because the furnace combustion process is affected by random disturbances more and it’s of nonlinearity, great inertia and coupling, so it is difficult to establish an accurate mode of controlled object, and achieve the ideal result by traditional control methods, which depend on the experience of the personnel operator to control the set values of lower level control loop. When the boundary conations change, which usually makes the technical specification actual values deviate the scope of target, and result decline in product quality, energy consumption increases. Quantitative feedback theory is a fashionable robust control theory rapidly developed in recent years, which has the advantage of engineering practicability, which don not need to know the precise mathematical model of controlled object. For the above, the quantitative feedback theory and fuzzy control technology are applied to reheating furnace control, and make research on these key problems including, temperature control, combustion control and optimizing ration of air to fuel. Specifically, this paper includes the main work as follows: First of all, this thesis has a profound research on combustion mechanism of reheating furnace, and using temperature combustion cascade control methods to control temperature automatically. Proposing establish furnace temperature model by experimental models, the least square method on the model parameters identification. According to the identification, a temperature controller is designed temperature design based on QFT. Meanwhile, using fuzzy control technology to improve the controller’s performance, and achieve online parameters self-tuning to improve the adaptability of the system. Second, we improve double cross limiting model slow response problems. After analyzing the relationship between combustion efficiency and air-fuel ratio, according to the problem of the best air/fuel excurses with fuel calorific value and changes in furnace conditions, optimization of air/fuel ratio's fuzzy controller assorting with the feed forward of the calorimeter based on temperature change and oxygen content of furnace flue. Combustion efficiency got improved. Finally, the control system simulation and performance analysis show that designed controller is robust on the furnace operating conditions change, system performance become well both in response and economy.
Based on the deep analysis of the reheating furnace characteristic, the reheating furnace temperature combustion control system has been designed, especially the optimizing design of Air/Fuel ratio and the improving of double-cross limit control model has great reference value both in academic research and practical applications in engineering.
引文
[1]池桂兴.工业炉节能技术[M].北京:冶金工业出版社, 1994.6.
[2]肖仕长.蓄热式燃烧技术在轧钢加热炉上的合理利用[J].四川冶金, 2008, 30(4): 40-43.
[3]蔡乔方.加热炉[M].北京:冶金工业出版社, 1994.4.
[4]荣莉,柴天佑,钱晓龙.加热炉过程控制技术的新策略—智能控制[J].控制与决策, 2000, 15(3): 269-273.
[5]孙德辉,史运涛.网络化控制系统-理论、技术及工程应用[M].北京:国防工业出版社,2008.5
[6] Lu Y.Z,Wlliams T.J. Energy savings and Productivity increase with computers-a case study of the steel ingot handling process[J]. Computers in Industry, 1983, 10(4): 1-18.
[7] Anton J,Branislav G,TomazK,etal.A simulation of heat transfer during billet transport[J]. Applied Thermal Engineering, 2002, 22(1): 873-886.
[8] H.E.Pike,S.J.Citron, Optimization study of a reheating furnace[J]. Automatic, 1970, 6(1): 41-50.
[9] T.A.Veslocki,C.C.Smith,C.D.Kelly. Automatic slab heating control at Inland’s 80-in.hots trip mill AISE Year Book [M], 1986, 54-60.
[10] R.A.Fadel. Integrated reheat furnace control system to improve productivity [J]. Iron &Steel Engineer, 1989, 66(3): 38-40.
[11] Y.Misaka,R.Takaharhi,A.Shinjo, metal. Computer control of a reheat furnace Kashima steel works’hot strip mill [J]. Iron& Steel Engineer, 1982, 59(5): 51-55.
[12] Shen F. Walking beam furnace supervisory control at Inland’s 80-in hot strip mill [J]. Iron & Steel Engineer, 1994, 71(7): 25-34.
[13]胡仁安.钢铁工业自动化的新技术(下)[J].冶金自动化, 2001,(2): 6-11.
[14]王继烈,范功友.轧钢加热炉计算机控制的现状与发展趋势[J].山东冶金, 1995, 17(2):11-13
[15]潘海鹏.基于智能控制的加热炉自动化系统[J].微计算机信息, 2004.4, (2): 33-35.
[16]杨伟.马钢H型轧机加热炉燃烧控制系统[J].系统与装置, 1999, (2): 27-30.
[17]张维.模糊神经网络在钢坯出炉温度建模和控制中的应用[D].重庆大学硕士论文, 2007.4.
[18]吕川.模糊控制用于加热炉控制[J].化工电子计算, 1982, (2): 65-69.
[19]商桂梅,焦吉成,张世建.板坯加热炉三维温度场数学模型系统的开发及应用[J].冶金自动化, 2009, 33(2):41-42.
[20]邬纳新,李彤,黄俊东.马钢热风炉残氧分析与优化燃烧技术[J].自动化仪表,2008, (7): 43-45
[21]吕勇哉.工业过程模型化及计算机控制[M].北京:化学工业出版社, 1986.
[22]池桂兴.工业炉节能技术[M].北京:冶金工业出版社, 1994.6.
[23]施仁,刘文江.自动化仪表与过程控制[M].北京:电子工业出版社, 1990.3.
[24]杨志.邓仁明等.轧钢加热炉的控制与节能[J].仪器仪表学报,2001,22(3): 438-439.
[25]萧得云,吕伯明.过程控制系统—应用、设计与整定[M].北京:清华大学出版社, 2004.
[26]邵裕森.过程控制及仪表[M].上海:上海交通大学出版社, 1995.7.
[27]于希宁,刘洁,田亮.一种基于炉膛压力分析的燃烧特征信号提取方法[J].电力科学与工程, 2009.2,25(2): 27-30.
[28]梁军.大型板坯加热炉中钢坯温度分布的软测量研究及实现[J].仪器仪表学报, 1999,2(2):81-83.
[29]程加堂,艾莉,熊伟等.钢坯三维温度场预报模型的建立[J].自动化博览, 2009.1,(1):75-76.
[30] A. D. Acharya, S. Chattopadhyay. Reheat furnace temperature control and performance at. Essar Steel [J]. Iron&Steel Engineer, 1998, 75(12): 31-36.
[31]刘日新,宁宝林.钢坯连续加热炉动态操作与优化控制的数学模型[J].钢铁研究学报,1992,4(3): 31-35.
[32] MacGregor JF,KourtiT. and Nomikos P. Analysis, monitoring and fault diagnosis of industrial processes using multivariate statistical projection methods[C]. Proceedings of 13th IFAC World Congress, San Francisco, USA, 1996.
[33]林涛,段文泽,李昌春.轧钢加热炉建模方法的比较研究[J].计算机仿真, 2008,25(3):95-99.
[34]李俊洪,林霞,刘勇.热轧板坯加热温度场数值模拟及应用[J].钢铁, 2009.1,44(1):44-46.
[35] Horowitz I. Survey of Quantitative Feedback Theory [J]. International Journal of Control, 1991, 53(2): 255-291.
[36]王杰,周永年.基于QFT的火电厂主汽温控制系统的设计与仿真[J].系统仿真学报, 2008,20(17): 4537-4543.
[37]王蕾. QFT在飞行控制系统中的应用[D].西北工业大学硕士论文, 2007.3.
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[41]周瀚.型钢加热炉系统中一种温度及空燃比控制方式研究[D].重庆大学硕士论文, 2006.5.
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[2]肖仕长.蓄热式燃烧技术在轧钢加热炉上的合理利用[J].四川冶金, 2008, 30(4): 40-43.
[3]蔡乔方.加热炉[M].北京:冶金工业出版社, 1994.4.
[4]荣莉,柴天佑,钱晓龙.加热炉过程控制技术的新策略—智能控制[J].控制与决策, 2000, 15(3): 269-273.
[5]孙德辉,史运涛.网络化控制系统-理论、技术及工程应用[M].北京:国防工业出版社,2008.5
[6] Lu Y.Z,Wlliams T.J. Energy savings and Productivity increase with computers-a case study of the steel ingot handling process[J]. Computers in Industry, 1983, 10(4): 1-18.
[7] Anton J,Branislav G,TomazK,etal.A simulation of heat transfer during billet transport[J]. Applied Thermal Engineering, 2002, 22(1): 873-886.
[8] H.E.Pike,S.J.Citron, Optimization study of a reheating furnace[J]. Automatic, 1970, 6(1): 41-50.
[9] T.A.Veslocki,C.C.Smith,C.D.Kelly. Automatic slab heating control at Inland’s 80-in.hots trip mill AISE Year Book [M], 1986, 54-60.
[10] R.A.Fadel. Integrated reheat furnace control system to improve productivity [J]. Iron &Steel Engineer, 1989, 66(3): 38-40.
[11] Y.Misaka,R.Takaharhi,A.Shinjo, metal. Computer control of a reheat furnace Kashima steel works’hot strip mill [J]. Iron& Steel Engineer, 1982, 59(5): 51-55.
[12] Shen F. Walking beam furnace supervisory control at Inland’s 80-in hot strip mill [J]. Iron & Steel Engineer, 1994, 71(7): 25-34.
[13]胡仁安.钢铁工业自动化的新技术(下)[J].冶金自动化, 2001,(2): 6-11.
[14]王继烈,范功友.轧钢加热炉计算机控制的现状与发展趋势[J].山东冶金, 1995, 17(2):11-13
[15]潘海鹏.基于智能控制的加热炉自动化系统[J].微计算机信息, 2004.4, (2): 33-35.
[16]杨伟.马钢H型轧机加热炉燃烧控制系统[J].系统与装置, 1999, (2): 27-30.
[17]张维.模糊神经网络在钢坯出炉温度建模和控制中的应用[D].重庆大学硕士论文, 2007.4.
[18]吕川.模糊控制用于加热炉控制[J].化工电子计算, 1982, (2): 65-69.
[19]商桂梅,焦吉成,张世建.板坯加热炉三维温度场数学模型系统的开发及应用[J].冶金自动化, 2009, 33(2):41-42.
[20]邬纳新,李彤,黄俊东.马钢热风炉残氧分析与优化燃烧技术[J].自动化仪表,2008, (7): 43-45
[21]吕勇哉.工业过程模型化及计算机控制[M].北京:化学工业出版社, 1986.
[22]池桂兴.工业炉节能技术[M].北京:冶金工业出版社, 1994.6.
[23]施仁,刘文江.自动化仪表与过程控制[M].北京:电子工业出版社, 1990.3.
[24]杨志.邓仁明等.轧钢加热炉的控制与节能[J].仪器仪表学报,2001,22(3): 438-439.
[25]萧得云,吕伯明.过程控制系统—应用、设计与整定[M].北京:清华大学出版社, 2004.
[26]邵裕森.过程控制及仪表[M].上海:上海交通大学出版社, 1995.7.
[27]于希宁,刘洁,田亮.一种基于炉膛压力分析的燃烧特征信号提取方法[J].电力科学与工程, 2009.2,25(2): 27-30.
[28]梁军.大型板坯加热炉中钢坯温度分布的软测量研究及实现[J].仪器仪表学报, 1999,2(2):81-83.
[29]程加堂,艾莉,熊伟等.钢坯三维温度场预报模型的建立[J].自动化博览, 2009.1,(1):75-76.
[30] A. D. Acharya, S. Chattopadhyay. Reheat furnace temperature control and performance at. Essar Steel [J]. Iron&Steel Engineer, 1998, 75(12): 31-36.
[31]刘日新,宁宝林.钢坯连续加热炉动态操作与优化控制的数学模型[J].钢铁研究学报,1992,4(3): 31-35.
[32] MacGregor JF,KourtiT. and Nomikos P. Analysis, monitoring and fault diagnosis of industrial processes using multivariate statistical projection methods[C]. Proceedings of 13th IFAC World Congress, San Francisco, USA, 1996.
[33]林涛,段文泽,李昌春.轧钢加热炉建模方法的比较研究[J].计算机仿真, 2008,25(3):95-99.
[34]李俊洪,林霞,刘勇.热轧板坯加热温度场数值模拟及应用[J].钢铁, 2009.1,44(1):44-46.
[35] Horowitz I. Survey of Quantitative Feedback Theory [J]. International Journal of Control, 1991, 53(2): 255-291.
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