ATP干馏炉温度控制系统研究
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摘要
随着油价的日益高涨,页岩炼油受到了越来越多的关注。在页岩炼油行业里,基于ATP炉的工艺是世界先进的页岩炼油干馏工艺。其ATP炉控制效果的优劣直接影响页岩油的产量,而温度控制又是ATP炉控制系统中的关键环节,因此有必要对页岩炼油过程中ATP炉的温度控制进行深入的研究。
本文以某页岩炼油厂的页岩炼油生产线为研究背景,阐述了ATP炉的结构组成和工作原理,消化研究了ATP炉的温度控制系统。并提出了ATP炉温度控制的难点：当进料率由于某些原因发生变化而导致ATP炉热负荷发生改变时,如何调节燃烧空气的补给率才能使ATP炉干馏区料床的温度保持在最佳的工艺温度。通过对ATP炉温度控制过程的分析得出：温度对象具有惯性、滞后的特征。同时由于在干馏过程中影响温度的因素比较复杂,很难用准确的数学模型对温度对象进行描述。为解决温度对象的特性对控制系统的影响,利用了内模控制结构简单、调整方针明确和抗干扰能力强的特点,采用了内模控制的方法设计ATP炉温度控制系统。为了克服对象与内部模型匹配之间存在的误差,在反馈回路中加入了滤波器。
最后利用了与所研究的ATP炉相同的控制系统——罗克韦尔公司的ControlLogix系列PLC,搭建实验台进行了仿真研究。同时利用了ControlLogix调试软件自带的趋势图功能,将本文设计的温度控制系统与传统PID控制进行比较,分析了滤波参数对系统性能的影响以及系统的扰动响应曲线。仿真结果表明,内模控制结构对ATP炉温度控制系统这一大惯性、纯滞后的系统具有良好的控制性能。
With the price of oil getting higher and higher, oil shale industry is received more and more concern. In the oil shale industry ATP is an advanced process. The output of shale oil is depended on the quality of control in ATP furnace especially the quality of temperature control. Therefore, it is necessary to research on temperature control of ATP furnace.
The thesis takes shale oil refining production line in shale oil refining factory as the background, and expounds the structure composition and working principle of ATP furnace. In the paper it is analyzed for ATP furnace temperature control system in detail and then it is put forward the difficulty in controlling temperature of ATP furnace. Namely while thermal load is changed since the feed rate is changed for some reason and then how to control the combustion air flow rate in order to keep the temperature of retort zone in ATP furnace as the best process temperature. It can be concluded that the temperature object itself has inertia and delay features. However, as the factors that influence the temperature during the oil shale retorting are complex, it is difficult to describe the temperature object using precise mathematical model. To avoid the effects of characteristics of the temperature object on the control system, the internal model control approach is used to design ATP furnace temperature control system, combined with the characteristics of internal model control for instance simple structure, clear reorientation and strong anti-interference ability. In order to overcome the matching error between object and internal model, filter is added in the feedback loop.
Finally, the author uses the ControlLogix PLC which is the same kind control system as ATP furnace to build an experimental model for a simulation study. Moreover, the temperature control system improved by this paper is compared with traditional PID control system by using trend function of ControlLogix programming and debugging software and also the effects of filter parameter on system performance and disturbance response curve of the system are analyzed. The emulation results show that internal model control structure has good performance for the temperature control system of ATP furnace with large inertia and pure lag.
本文以某页岩炼油厂的页岩炼油生产线为研究背景,阐述了ATP炉的结构组成和工作原理,消化研究了ATP炉的温度控制系统。并提出了ATP炉温度控制的难点：当进料率由于某些原因发生变化而导致ATP炉热负荷发生改变时,如何调节燃烧空气的补给率才能使ATP炉干馏区料床的温度保持在最佳的工艺温度。通过对ATP炉温度控制过程的分析得出：温度对象具有惯性、滞后的特征。同时由于在干馏过程中影响温度的因素比较复杂,很难用准确的数学模型对温度对象进行描述。为解决温度对象的特性对控制系统的影响,利用了内模控制结构简单、调整方针明确和抗干扰能力强的特点,采用了内模控制的方法设计ATP炉温度控制系统。为了克服对象与内部模型匹配之间存在的误差,在反馈回路中加入了滤波器。
最后利用了与所研究的ATP炉相同的控制系统——罗克韦尔公司的ControlLogix系列PLC,搭建实验台进行了仿真研究。同时利用了ControlLogix调试软件自带的趋势图功能,将本文设计的温度控制系统与传统PID控制进行比较,分析了滤波参数对系统性能的影响以及系统的扰动响应曲线。仿真结果表明,内模控制结构对ATP炉温度控制系统这一大惯性、纯滞后的系统具有良好的控制性能。
With the price of oil getting higher and higher, oil shale industry is received more and more concern. In the oil shale industry ATP is an advanced process. The output of shale oil is depended on the quality of control in ATP furnace especially the quality of temperature control. Therefore, it is necessary to research on temperature control of ATP furnace.
The thesis takes shale oil refining production line in shale oil refining factory as the background, and expounds the structure composition and working principle of ATP furnace. In the paper it is analyzed for ATP furnace temperature control system in detail and then it is put forward the difficulty in controlling temperature of ATP furnace. Namely while thermal load is changed since the feed rate is changed for some reason and then how to control the combustion air flow rate in order to keep the temperature of retort zone in ATP furnace as the best process temperature. It can be concluded that the temperature object itself has inertia and delay features. However, as the factors that influence the temperature during the oil shale retorting are complex, it is difficult to describe the temperature object using precise mathematical model. To avoid the effects of characteristics of the temperature object on the control system, the internal model control approach is used to design ATP furnace temperature control system, combined with the characteristics of internal model control for instance simple structure, clear reorientation and strong anti-interference ability. In order to overcome the matching error between object and internal model, filter is added in the feedback loop.
Finally, the author uses the ControlLogix PLC which is the same kind control system as ATP furnace to build an experimental model for a simulation study. Moreover, the temperature control system improved by this paper is compared with traditional PID control system by using trend function of ControlLogix programming and debugging software and also the effects of filter parameter on system performance and disturbance response curve of the system are analyzed. The emulation results show that internal model control structure has good performance for the temperature control system of ATP furnace with large inertia and pure lag.
引文
1.美国能源部能源信息署.国际能源展望2004[M],北京：清华大学出版社,2004,1-55.
2.张建民,谢忠波.油页岩资源前景广阔[J],中国化工报,2009,2(6)：12-14.
3.杨帆.油页岩的热转化利用[D],西北大学,2009.
4.侯祥麟.中国页岩油工业[M],北京：石油工业出版社,1984,22-35.
5.钱家麟,王剑秋,李术元.世界油页岩综述[J],中国能源,2006,28(8)：16-19.
6. Cha C.L, Me Carthy H.E. In situ oil shale retorting, in Allerd V.D. Oil shale processing technology [M], East Brunswick, New Jersey, USA:The Center for professional advancement,1982,189-216.
7. B aughman G.L. Synthetic fuels data handbook, second edition [M], Denver, USA: Cameron Engineering Inc.,1978,126-128.
8. Veiderma M. Estonian oil shale-Resources and usage [J], Oil Shale,2003,20(35): 295-303.
9.张秋民,关君,何德民.几种典型的油页岩干馏技术[J],化工学报,2006,57(1)：126-130.
10.高健.世界各国油页岩干馏技术简介[J],煤炭加工与综合利用,2003(2)：44-46.
11.钱家麟,王剑秋,李术元.世界油页岩资源利用和发展趋势[J],吉林大学学报,2006,36(6)：877-887.
12.钱家麟,尹亮.油页岩—石油的补充能源[M],北京：中国石化出版社,2008,137-139.
13.GOLUBEV N. Solid heat carrier technology for oil shale retorting [J], Oil Shale,2003, 20(3):324-332.
14.JABER.J.O., SLADEK T.A., MERNITZ S., TARAWNEH T M. Future Policies and Strategies for Oil Shale Development in Jordan [J], Jordan Journal of Mechanical and Industrial Engineering,2008,2(1):31-44.
15.韩向新,姜秀民,崔志钢等.油页岩半焦特性[J],化工学报,2006,59(2)：221-230.
16.刘伯谦.油页岩及其流化床燃烧[M],长春：吉林科学技术出版社,1999,30-33.
17.徐俭臣.页岩硫化干馏炼油技术的研究[J],黑龙江科技信息,2004,7：38.
18.王再英,刘怀霞,陈毅静.过程控制系统与仪表[M],北京：机械工业出版社,2006,35-37.
19.徐兵.过程控制[M],北京：机械工业出版社,2004,109-118.
20.卢京潮.自动控制原理[M],西安：西北工业大学出版社,2004,9.
21.肖术骏,陶睿,王秀,郭佩佩,朱学峰.IMC-PID在水厂出水浊度控制中的仿真研究[J],自动化与仪表,2009(1)：36-38.
22.王树青.先进控制技术及应用[M],北京：化学工业出版社,2001,44-48.
23.李少远,王景成.智能控制[M],北京：机械工业出版社,2004,76-79.
24.蔡小玲,汪小帆,王执铨.内模控制与PI控制[J],南京理工大学学报,2002,26(4)：47-51.
25. Smith O J. A Controller to Overcome Dead Time [J], ISAJ,1959,6(2):28-33.
26.赵耀.内模控制发展综述[J],信息与控制,2000,29(6)：526-531.
27. Garcia CE, Morari M. Internal Model Control,1 A, Unifying Review and Some New Results [J], Ind. Eng. Chem. Process Des. Dev,1982,21(2):308-323.
28.梅华,孙建平,李鹏.内模控制系统的鲁棒机理分析[J],电力情报,2001,3：46-48.
29.周涌等.内模控制研究的新发展[J],控制理论与应用,2004,6：5-6.
30.谢文滔.基于改进型内模控制技术在钢厂温控系统中的应用[J],自动化技术与应用,2011,30(3)：15-17.
31. Carlos E. Garcia, Manfred Morari. Internal Model Control-1:a unifying review and some new results [J], Industrial Engineering Chemistry Process Design and Development,1982,21(2):308-323.
32. Sachin C. Patwardhan, K. P. Madhavan. Nonlinear internal model control using quadratic prediction models [J], Computers & Chemical Engineering,1998,22(5): 587-601.
33. Q. Hu, P. Saha, G. P. Rangaiah. Experimental evaluation of an augmented IMC for nonlinear systems [J], Control Engineering Practice,2000,8(10):1167-1176.
34. E. P. Nahas, M.. A. Henson, D. E. Seborg. Nonlinear internal model control strategy for neural network models [J], Computers & Chemical Engineering,1992,16(12): 1039-1057.
35.K.J. Hunt, D. Sbarbaro. Neural networks for nonlinear internal model control [J], IEE Proceedings-Control Theory and Applications,1991,138(5):431-438.
36.吕朝霞,吴晓蓓,郭健,胡维礼,胡寿松.基于小波网络的非线性内模控制[J],控制与决策,2001,16(1)：65-68.
37. Martin Pottmann, H. Peter Jorgl. Radial basis function networks for internal model control [J], Applied Mathematics and Computation,1995,70(2-35):283-298.
38.Han-Xiong Li, Hua Deng. An approximate internal model-based neural control for unknown nonlinear discrete processes [J], IEEE Transactions on Neural Networks,2006, 17(3):659-670.
39.金晓明,荣冈,王树青.基于模糊模型的非线性内模控制策略研究[J],控制与决策,1997,12(3)：228-233.
40. Janos Abonyi, Ferenc Szeifert. Fuzzy modeling with multivariate membership functions: gray-box identification and control design [J], IEEE Transactions on Systems, Man, and Cybernetics, Part B,2001,31(5):755-767.
41.侯媛彬,汪梅,王立琦.系统辨识及其MATLAB仿真[M],北京：科学出版社,2004,171-174.
42.王东风,王剑东,韩璞等.基于内模原理的PID控制器参数整定[J],华北电力大学学报,2003,3(4)：92-93.
43.王伟.广义预测控制理论及其应用[M],北京：科学出版社,1998,99-105.
44.郑轲,孙一康.时滞过程控制算法分析[J],北京科技大学学报,2000,22(5)：486-488.
45.Economou C. G. Internal Model Control-5:extension to nonlinear systems [J], Industrial Engineering Chemistry Process Design and Development,1986,25(2): 403-411.
46.赵辉.基于内模控制原理的PID控制器设计[D],天津：天津大学,2005.
47.刘开培,郑世喜,陈华.基于Taylor展开的纯滞后系统增益自适应内模PID控制[J],电气自动化,2002,1：23-25.
48.邓李ControlLogix系统使用手册[M],北京：机械工业出版社,2008,2-3.
49.钱晓龙,苑旭东,刘婷等ControlLogix系统水泥行业自动化应用培训教程[M],北京：机械工业出版社,2009,80-88.
2.张建民,谢忠波.油页岩资源前景广阔[J],中国化工报,2009,2(6)：12-14.
3.杨帆.油页岩的热转化利用[D],西北大学,2009.
4.侯祥麟.中国页岩油工业[M],北京：石油工业出版社,1984,22-35.
5.钱家麟,王剑秋,李术元.世界油页岩综述[J],中国能源,2006,28(8)：16-19.
6. Cha C.L, Me Carthy H.E. In situ oil shale retorting, in Allerd V.D. Oil shale processing technology [M], East Brunswick, New Jersey, USA:The Center for professional advancement,1982,189-216.
7. B aughman G.L. Synthetic fuels data handbook, second edition [M], Denver, USA: Cameron Engineering Inc.,1978,126-128.
8. Veiderma M. Estonian oil shale-Resources and usage [J], Oil Shale,2003,20(35): 295-303.
9.张秋民,关君,何德民.几种典型的油页岩干馏技术[J],化工学报,2006,57(1)：126-130.
10.高健.世界各国油页岩干馏技术简介[J],煤炭加工与综合利用,2003(2)：44-46.
11.钱家麟,王剑秋,李术元.世界油页岩资源利用和发展趋势[J],吉林大学学报,2006,36(6)：877-887.
12.钱家麟,尹亮.油页岩—石油的补充能源[M],北京：中国石化出版社,2008,137-139.
13.GOLUBEV N. Solid heat carrier technology for oil shale retorting [J], Oil Shale,2003, 20(3):324-332.
14.JABER.J.O., SLADEK T.A., MERNITZ S., TARAWNEH T M. Future Policies and Strategies for Oil Shale Development in Jordan [J], Jordan Journal of Mechanical and Industrial Engineering,2008,2(1):31-44.
15.韩向新,姜秀民,崔志钢等.油页岩半焦特性[J],化工学报,2006,59(2)：221-230.
16.刘伯谦.油页岩及其流化床燃烧[M],长春：吉林科学技术出版社,1999,30-33.
17.徐俭臣.页岩硫化干馏炼油技术的研究[J],黑龙江科技信息,2004,7：38.
18.王再英,刘怀霞,陈毅静.过程控制系统与仪表[M],北京：机械工业出版社,2006,35-37.
19.徐兵.过程控制[M],北京：机械工业出版社,2004,109-118.
20.卢京潮.自动控制原理[M],西安：西北工业大学出版社,2004,9.
21.肖术骏,陶睿,王秀,郭佩佩,朱学峰.IMC-PID在水厂出水浊度控制中的仿真研究[J],自动化与仪表,2009(1)：36-38.
22.王树青.先进控制技术及应用[M],北京：化学工业出版社,2001,44-48.
23.李少远,王景成.智能控制[M],北京：机械工业出版社,2004,76-79.
24.蔡小玲,汪小帆,王执铨.内模控制与PI控制[J],南京理工大学学报,2002,26(4)：47-51.
25. Smith O J. A Controller to Overcome Dead Time [J], ISAJ,1959,6(2):28-33.
26.赵耀.内模控制发展综述[J],信息与控制,2000,29(6)：526-531.
27. Garcia CE, Morari M. Internal Model Control,1 A, Unifying Review and Some New Results [J], Ind. Eng. Chem. Process Des. Dev,1982,21(2):308-323.
28.梅华,孙建平,李鹏.内模控制系统的鲁棒机理分析[J],电力情报,2001,3：46-48.
29.周涌等.内模控制研究的新发展[J],控制理论与应用,2004,6：5-6.
30.谢文滔.基于改进型内模控制技术在钢厂温控系统中的应用[J],自动化技术与应用,2011,30(3)：15-17.
31. Carlos E. Garcia, Manfred Morari. Internal Model Control-1:a unifying review and some new results [J], Industrial Engineering Chemistry Process Design and Development,1982,21(2):308-323.
32. Sachin C. Patwardhan, K. P. Madhavan. Nonlinear internal model control using quadratic prediction models [J], Computers & Chemical Engineering,1998,22(5): 587-601.
33. Q. Hu, P. Saha, G. P. Rangaiah. Experimental evaluation of an augmented IMC for nonlinear systems [J], Control Engineering Practice,2000,8(10):1167-1176.
34. E. P. Nahas, M.. A. Henson, D. E. Seborg. Nonlinear internal model control strategy for neural network models [J], Computers & Chemical Engineering,1992,16(12): 1039-1057.
35.K.J. Hunt, D. Sbarbaro. Neural networks for nonlinear internal model control [J], IEE Proceedings-Control Theory and Applications,1991,138(5):431-438.
36.吕朝霞,吴晓蓓,郭健,胡维礼,胡寿松.基于小波网络的非线性内模控制[J],控制与决策,2001,16(1)：65-68.
37. Martin Pottmann, H. Peter Jorgl. Radial basis function networks for internal model control [J], Applied Mathematics and Computation,1995,70(2-35):283-298.
38.Han-Xiong Li, Hua Deng. An approximate internal model-based neural control for unknown nonlinear discrete processes [J], IEEE Transactions on Neural Networks,2006, 17(3):659-670.
39.金晓明,荣冈,王树青.基于模糊模型的非线性内模控制策略研究[J],控制与决策,1997,12(3)：228-233.
40. Janos Abonyi, Ferenc Szeifert. Fuzzy modeling with multivariate membership functions: gray-box identification and control design [J], IEEE Transactions on Systems, Man, and Cybernetics, Part B,2001,31(5):755-767.
41.侯媛彬,汪梅,王立琦.系统辨识及其MATLAB仿真[M],北京：科学出版社,2004,171-174.
42.王东风,王剑东,韩璞等.基于内模原理的PID控制器参数整定[J],华北电力大学学报,2003,3(4)：92-93.
43.王伟.广义预测控制理论及其应用[M],北京：科学出版社,1998,99-105.
44.郑轲,孙一康.时滞过程控制算法分析[J],北京科技大学学报,2000,22(5)：486-488.
45.Economou C. G. Internal Model Control-5:extension to nonlinear systems [J], Industrial Engineering Chemistry Process Design and Development,1986,25(2): 403-411.
46.赵辉.基于内模控制原理的PID控制器设计[D],天津：天津大学,2005.
47.刘开培,郑世喜,陈华.基于Taylor展开的纯滞后系统增益自适应内模PID控制[J],电气自动化,2002,1：23-25.
48.邓李ControlLogix系统使用手册[M],北京：机械工业出版社,2008,2-3.
49.钱晓龙,苑旭东,刘婷等ControlLogix系统水泥行业自动化应用培训教程[M],北京：机械工业出版社,2009,80-88.