化工学报 ›› 2019, Vol. 70 ›› Issue (5): 1848-1857.DOI: 10.11949/j.issn.0438-1157.20181306
收稿日期:
2018-11-12
修回日期:
2019-01-22
出版日期:
2019-05-05
发布日期:
2019-05-05
通讯作者:
罗雄麟
作者简介:
<named-content content-type="corresp-name">黄冬</named-content>(1990—),男,博士研究生,讲师,<email>huangdong2318@163.com</email>|罗雄麟(1963—),男,博士,教授,<email>luoxl@cup.edu.cn</email>
基金资助:
Dong HUANG1,2(),Xionglin LUO1()
Received:
2018-11-12
Revised:
2019-01-22
Online:
2019-05-05
Published:
2019-05-05
Contact:
Xionglin LUO
摘要:
化工过程出现大范围的工况变化时,复杂的迁移控制策略会带来一定的操作不确定性,因此需要对控制策略进行选择判定。考虑到直接估计工况变化过程生产指标变化量带来的判定误差,引入了中间变量,提出了基于中间变量的控制策略选择判定方法,并分析给出了构建中间变量的基本准则。进而通过对某实际乙烯精馏塔工况变化过程的仿真研究,说明了中间变量的引入能够很大程度地降低对生产指标的估计误差,验证了基于中间变量的控制策略选择判定方法的可用性。
中图分类号:
黄冬, 罗雄麟. 化工过程大范围工况变化的工况迁移控制策略判定[J]. 化工学报, 2019, 70(5): 1848-1857.
Dong HUANG, Xionglin LUO. Judgement of process transition control strategies for large-range conditions change of chemical processes[J]. CIESC Journal, 2019, 70(5): 1848-1857.
Transition factor | Value (p ub) |
---|---|
maximum increment of feed flowrate (p 1) | 21.88% |
maximum increment of ethylene component (p 2) | 3.934% |
maximum decrement of feed flowrate (p 3) | 22.54% |
maximum decrement of ethylene component (p 4) | 4.691% |
表1 不同类型工况迁移因素最大允许值
Table 1 Maximum value of different transition factors
Transition factor | Value (p ub) |
---|---|
maximum increment of feed flowrate (p 1) | 21.88% |
maximum increment of ethylene component (p 2) | 3.934% |
maximum decrement of feed flowrate (p 3) | 22.54% |
maximum decrement of ethylene component (p 4) | 4.691% |
Normalized transition factor | Potential intermediate variable | Production index/% | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
| | | | | | | | | | | | |
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
0.2 | 0.04441 | 0.04386 | 0.05349 | 0.04806 | 0.00054 | 0.00001 | 0.00924 | 0.00403 | 0.001930 | |||
0.4 | 0.08882 | 0.08771 | 0.10711 | 0.09650 | 0.00104 | 0.00002 | 0.01785 | 0.00810 | 0.003903 | |||
0.6 | 0.13323 | 0.13157 | 0.16086 | 0.14534 | 0.00150 | 0.00003 | 0.02591 | 0.01220 | 0.005904 | |||
0.8 | 0.17765 | 0.17543 | 0.21474 | 0.19458 | 0.00192 | 0.00004 | 0.03349 | 0.01633 | 0.007933 | |||
1.0 | 0.22206 | 0.21929 | 0.26877 | 0.24421 | 0.00232 | 0.00005 | 0.04063 | 0.02049 | 0.010000 | |||
0.2 | 0.01072 | 0.04708 | 0.00475 | 0.00289 | 0.01072 | 0.04708 | 0.00475 | 0.00289 | 0.002173 | |||
0.4 | 0.02143 | 0.09415 | 0.00908 | 0.00552 | 0.02143 | 0.09415 | 0.00908 | 0.00552 | 0.004098 | |||
0.6 | 0.03215 | 0.14123 | 0.01294 | 0.00788 | 0.03215 | 0.14123 | 0.01294 | 0.00788 | 0.006070 | |||
0.8 | 0.04287 | 0.18831 | 0.01628 | 0.00993 | 0.04287 | 0.18831 | 0.01628 | 0.00993 | 0.008063 | |||
1.0 | 0.05358 | 0.23539 | 0.01905 | 0.01163 | 0.05358 | 0.23539 | 0.01905 | 0.01163 | 0.010000 | |||
0.2 | 0.04575 | 0.04518 | 0.05498 | 0.04910 | 0.00061 | 0.00001 | 0.01027 | 0.00412 | 0.002076 | |||
0.4 | 0.09150 | 0.09035 | 0.10982 | 0.09781 | 0.00128 | 0.00002 | 0.02142 | 0.00821 | 0.004089 | |||
0.6 | 0.13725 | 0.13553 | 0.16455 | 0.14611 | 0.00202 | 0.00003 | 0.03359 | 0.01227 | 0.006090 | |||
0.8 | 0.18300 | 0.18070 | 0.21915 | 0.19403 | 0.00284 | 0.00003 | 0.04696 | 0.01629 | 0.008064 | |||
1.0 | 0.22876 | 0.22588 | 0.27364 | 0.24155 | 0.00376 | 0.00004 | 0.06174 | 0.02029 | 0.010000 | |||
0.2 | 0.01278 | 0.05614 | 0.00616 | 0.00374 | 0.01048 | 0.04603 | 0.00616 | 0.00374 | 0.002171 | |||
0.4 | 0.02555 | 0.11227 | 0.01281 | 0.00777 | 0.02095 | 0.09206 | 0.01281 | 0.00777 | 0.004096 | |||
0.6 | 0.03833 | 0.16841 | 0.01990 | 0.01205 | 0.03143 | 0.13810 | 0.01990 | 0.01205 | 0.006068 | |||
0.8 | 0.05111 | 0.22455 | 0.02738 | 0.01658 | 0.04191 | 0.18413 | 0.02738 | 0.01658 | 0.008061 | |||
1.0 | 0.06389 | 0.28068 | 0.03521 | 0.02131 | 0.05239 | 0.23016 | 0.03521 | 0.02131 | 0.010000 |
表2 不同工况迁移因素作用下潜在中间变量和生产指标的真实数据
Table 2 Data of potential intermediate variables and production index with different transition factors
Normalized transition factor | Potential intermediate variable | Production index/% | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
| | | | | | | | | | | | |
0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
0.2 | 0.04441 | 0.04386 | 0.05349 | 0.04806 | 0.00054 | 0.00001 | 0.00924 | 0.00403 | 0.001930 | |||
0.4 | 0.08882 | 0.08771 | 0.10711 | 0.09650 | 0.00104 | 0.00002 | 0.01785 | 0.00810 | 0.003903 | |||
0.6 | 0.13323 | 0.13157 | 0.16086 | 0.14534 | 0.00150 | 0.00003 | 0.02591 | 0.01220 | 0.005904 | |||
0.8 | 0.17765 | 0.17543 | 0.21474 | 0.19458 | 0.00192 | 0.00004 | 0.03349 | 0.01633 | 0.007933 | |||
1.0 | 0.22206 | 0.21929 | 0.26877 | 0.24421 | 0.00232 | 0.00005 | 0.04063 | 0.02049 | 0.010000 | |||
0.2 | 0.01072 | 0.04708 | 0.00475 | 0.00289 | 0.01072 | 0.04708 | 0.00475 | 0.00289 | 0.002173 | |||
0.4 | 0.02143 | 0.09415 | 0.00908 | 0.00552 | 0.02143 | 0.09415 | 0.00908 | 0.00552 | 0.004098 | |||
0.6 | 0.03215 | 0.14123 | 0.01294 | 0.00788 | 0.03215 | 0.14123 | 0.01294 | 0.00788 | 0.006070 | |||
0.8 | 0.04287 | 0.18831 | 0.01628 | 0.00993 | 0.04287 | 0.18831 | 0.01628 | 0.00993 | 0.008063 | |||
1.0 | 0.05358 | 0.23539 | 0.01905 | 0.01163 | 0.05358 | 0.23539 | 0.01905 | 0.01163 | 0.010000 | |||
0.2 | 0.04575 | 0.04518 | 0.05498 | 0.04910 | 0.00061 | 0.00001 | 0.01027 | 0.00412 | 0.002076 | |||
0.4 | 0.09150 | 0.09035 | 0.10982 | 0.09781 | 0.00128 | 0.00002 | 0.02142 | 0.00821 | 0.004089 | |||
0.6 | 0.13725 | 0.13553 | 0.16455 | 0.14611 | 0.00202 | 0.00003 | 0.03359 | 0.01227 | 0.006090 | |||
0.8 | 0.18300 | 0.18070 | 0.21915 | 0.19403 | 0.00284 | 0.00003 | 0.04696 | 0.01629 | 0.008064 | |||
1.0 | 0.22876 | 0.22588 | 0.27364 | 0.24155 | 0.00376 | 0.00004 | 0.06174 | 0.02029 | 0.010000 | |||
0.2 | 0.01278 | 0.05614 | 0.00616 | 0.00374 | 0.01048 | 0.04603 | 0.00616 | 0.00374 | 0.002171 | |||
0.4 | 0.02555 | 0.11227 | 0.01281 | 0.00777 | 0.02095 | 0.09206 | 0.01281 | 0.00777 | 0.004096 | |||
0.6 | 0.03833 | 0.16841 | 0.01990 | 0.01205 | 0.03143 | 0.13810 | 0.01990 | 0.01205 | 0.006068 | |||
0.8 | 0.05111 | 0.22455 | 0.02738 | 0.01658 | 0.04191 | 0.18413 | 0.02738 | 0.01658 | 0.008061 | |||
1.0 | 0.06389 | 0.28068 | 0.03521 | 0.02131 | 0.05239 | 0.23016 | 0.03521 | 0.02131 | 0.010000 |
Number | Normalize transition factor | Actual index (judgement) | Direct estimation | Indirect estimation | |||||
---|---|---|---|---|---|---|---|---|---|
| | | | Estimated index (judgement) | Result | Estimated index (judgement) | Result | ||
1 | 0.5 | 0.45 | 0.00886 (C) | 0.00950 (C) | true | 0.00868 (C) | true | ||
2 | 0.5 | 0.55 | 0.00955 (C) | 0.01050 (T) | false | 0.00951 (C) | true | ||
3 | 0.5 | 0.5 | 0.00934 (C) | 0.01000 (T) | false | 0.00930 (C) | true | ||
4 | 0.45 | 0.5 | 0.00856 (C) | 0.00950 (C) | true | 0.00860 (C) | true | ||
5 | 0.55 | 0.5 | 0.00981 (C) | 0.01050 (T) | false | 0.00979 (C) | true | ||
6 | 0.5 | 0.45 | 0.01015 (T) | 0.00957 (C) | false | 0.01030 (T) | true | ||
7 | 0.5 | 0.55 | 0.01105 (T) | 0.01058 (T) | true | 0.01090 (T) | true | ||
8 | 0.5 | 0.5 | 0.01052 (T) | 0.01007 (T) | true | 0.01039 (T) | true | ||
9 | 0.45 | 0.5 | 0.00993 (C) | 0.00957 (C) | true | 0.00990 (C) | true | ||
10 | 0.55 | 0.5 | 0.01117 (T) | 0.01058 (T) | true | 0.01089 (T) | true |
表3 控制策略选择判定结果验证
Table 3 Verification of judgement of control strategies
Number | Normalize transition factor | Actual index (judgement) | Direct estimation | Indirect estimation | |||||
---|---|---|---|---|---|---|---|---|---|
| | | | Estimated index (judgement) | Result | Estimated index (judgement) | Result | ||
1 | 0.5 | 0.45 | 0.00886 (C) | 0.00950 (C) | true | 0.00868 (C) | true | ||
2 | 0.5 | 0.55 | 0.00955 (C) | 0.01050 (T) | false | 0.00951 (C) | true | ||
3 | 0.5 | 0.5 | 0.00934 (C) | 0.01000 (T) | false | 0.00930 (C) | true | ||
4 | 0.45 | 0.5 | 0.00856 (C) | 0.00950 (C) | true | 0.00860 (C) | true | ||
5 | 0.55 | 0.5 | 0.00981 (C) | 0.01050 (T) | false | 0.00979 (C) | true | ||
6 | 0.5 | 0.45 | 0.01015 (T) | 0.00957 (C) | false | 0.01030 (T) | true | ||
7 | 0.5 | 0.55 | 0.01105 (T) | 0.01058 (T) | true | 0.01090 (T) | true | ||
8 | 0.5 | 0.5 | 0.01052 (T) | 0.01007 (T) | true | 0.01039 (T) | true | ||
9 | 0.45 | 0.5 | 0.00993 (C) | 0.00957 (C) | true | 0.00990 (C) | true | ||
10 | 0.55 | 0.5 | 0.01117 (T) | 0.01058 (T) | true | 0.01089 (T) | true |
1 | 杨友麒, 项曙光 . 化工过程模拟与优化[M]. 北京:化学工业出版社, 2006. |
Yang Y L , Xiang S G . Modeling and Optimization of Chemical Processes[M]. Beijing:Chemical Industry Press, 2006. | |
2 | 罗祎青, 胡尊燕, 袁希钢 . 复杂化工过程系统的能值计算方法[J]. 化工学报, 2013, 64(1): 311-317. |
Luo Y Q , Hu Z Y , Yuan X G . Method for calculating stream energy in complex chemical process systems[J]. CIESC Journal, 2013, 64(1): 311-317. | |
3 | 许锋, 蒋慧蓉, 王锐,等 . 化工过程总体裕量与控制性能的权衡优化[J]. 化工学报, 2014, 65(4): 1303-1309. |
Xu F , Jiang H R , Wang R , et al . Tradeoff between whole margin and control performance for chemical process[J]. CIESC Journal, 2014, 65(4): 1303-1309. | |
4 | Huang D , Luo X L . Process transition based on dynamic optimization with the case of a throughput fluctuating ethylene column[J]. Industrial & Engineering Chemistry Research, 2018, 57(18): 6292-6302. |
5 | Chachuat B , Singer A B , Barton P I . Global mixed-integer dynamic optimization[J]. AIChE Journal, 2010, 51(8): 2235-2253. |
6 | Chu Y , You F . Integrated scheduling and dynamic optimization of complex batch processes with general network structure using a generalized benders decomposition approach[J]. Industrial & Engineering Chemistry Research, 2013, 52(23): 7867-7885. |
7 | 罗雄麟, 夏车奎, 孙琳 . 有旁路换热网络全周期节能的动态优化控制实现方法[J]. 化工学报, 2013, 64(4): 1340-1350. |
Luo X L , Xia C K , Sun L . A dynamic optimization control approach of life cycle energy saving for heat exchanger network with bypasses[J]. CIESC Journal, 2013, 64(4): 1340-1350. | |
8 | Huntington G T , Rao A V . Comparison of global and local collocation methods for optimal control[J]. Journal of Guidance,Control, and Dynamics, 2008, 31(2): 432-436. |
9 | Logsdon J S , Biegler L T . Accurate solution of differential-algebraic optimization problems[J]. Industrial & Engineering Chemistry Research, 1989, 28(11): 1628-1639. |
10 | Schlegel M , Marquardt W . Detection and exploitation of the control switching structure in the solution of dynamic optimization problems[J]. Journal of Process Control, 2006, 16(3): 275-290. |
11 | Li G D , Liu P , Liu X G . A control parameterization approach with variable time nodes for optimal control problems[J]. Asian Journal of Control, 2016, 18(3): 976-984. |
12 | Biegler L T . Solution of dynamic optimization problems by successive quadratic programming and orthogonal collocation[J]. Computers & Chemical Engineering, 1984, 8(3): 243-247. |
13 | Morison K R , Sargent R W H . Optimization of multistage processes described by differential-algebraic equations[C]//Proceedings of the Fourth IIMAS Workshop. Numerical Analysis. Heidelberg, Berlin: Springer, 1986: 86-102. |
14 | Cuthrell J E , Biegler L T . On the optimization of differential-algebraic process systems[J]. AIChE Journal, 1987, 33(8): 1257-1270. |
15 | Cuthrell J E , Biegler L T . Simultaneous optimization and solution methods for batch reactor control profiles[J]. Computers & Chemical Engineering, 1989, 13(1/2): 49-62. |
16 | Tanartkit P , Biegler L T . A nested, simultaneous approach for dynamic optimization problems(II): The outer problem[J]. Computers & Chemical Engineering, 1997, 21(12): 1365-1388. |
17 | Cervantes A M , Biegler L T . A stable elemental decomposition for dynamic process optimization[J]. Journal of Computational and Applied Mathematics, 2000, 120(1/2): 41-57. |
18 | Cervantes A M , Wächter A , Tütüncü R H , et al . A reduced space interior point strategy for optimization of differential algebraic systems[J]. Computers & Chemical Engineering, 2000, 24(1): 39-51. |
19 | Biegler L T , Cervantes A M , Wächter A . Advances in simultaneous strategies for dynamic process optimization[J]. Chemical Engineering Science, 2002, 57(4): 575-593. |
20 | Kameswaran S , Staus G , Biegler L T . Parameter estimation of core flood and reservoir models[J]. Computers & Chemical Engineering, 2005, 29(8): 1787-1800. |
21 | Kameswaran S , Biegler L T . Simultaneous dynamic optimization strategies: recent advances and challenges[J]. Computers & Chemical Engineering, 2006, 30(10/11/12): 1560-1575. |
22 | Zhao Y , Tsiotras P . Density functions for mesh refinement in numerical optimal control[J]. Journal of Guidance, Control, and Dynamics, 2011, 34(1): 271-277. |
23 | Darby C L , Hager W W , Rao A V . An hp-adaptive pseudospectral method for solving optimal control problems[J]. Optimal Control Applications and Methods, 2011, 32(4): 476-502. |
24 | Lazutkin E , Geletu A , Li P . An approach to determining the number of time intervals for solving dynamic optimization problems[J]. Industrial & Engineering Chemistry Research, 2018, 57(12): 4340-4350. |
25 | Fikar M , Latifi M A , Fournier F , et al . Control vector parametrisation versus iterative dynamic programming in dynamic optimisation of a distillation column[J]. Computers & Chemical Engineering, 1998, 22(12): S625-S628. |
26 | Fikar M , Latifi M A , Corriou J P , et al . CVP-based optimal control of an industrial depropanizer column[J]. Computers & Chemical Engineering, 2000, 24(2): 909-915. |
27 | Schlegel M , Marquardt W . Detection and exploitation of the control switching structure in the solution of dynamic optimization problems[J]. Journal of Process Control, 2006, 16(3): 275-290. |
28 | 王平, 田学民 . 一种改进的CVP方法及其在动态优化中的应用[J]. 控制与决策, 2009, 24(11): 1757-1760. |
Wang P , Tian X M . Enhanced control vector parameterization method and its application in dynamic optimization[J]. Control and Design, 2009, 24(11): 1757-1760. | |
29 | 李国栋 . 基于控制向量参数化的动态优化研究[D]. 杭州:浙江大学, 2015. |
Li G D . Control vector parameterization based dynamic optimization research[D]. Hangzhou:Zhejiang University, 2015. | |
30 | Chen X , Du W L , Tianfield H , et al . Dynamic optimization of industrial processes with nonuniform discretization-based control vector parameterization[J]. IEEE Transactions on Automation Science & Engineering, 2017, 11(4): 1289-1299. |
31 | Wang L , Liu X , Zhang Z . A new sensitivity-based adaptive control vector parameterization approach for dynamic optimization of bioprocesses[J]. Bioprocess & Biosystems Engineering, 2017, 40(2): 181-189. |
32 | Tian J , Zhang P P , Wang Y L , et al . Control vector parameterization based adaptive invasive weed optimization for dynamic processes[J]. Chemical Engineering & Technology, 2018, 41(5): 964-974. |
33 | 黄冬, 赵民帅, 罗雄麟 . 乙烯精馏塔控制中降液管时滞效应影响分析[J]. 化工学报, 2016, 67(11): 4696-4704. |
Huang D , Zhao M S , Luo X L . Analyzing time-lag effect of downcomer for control of ethylene column[J]. CIESC Journal, 2016, 67(11): 4696-4704. | |
34 | Huang D , Zhao X Y , Luo X L . Trade-off between energy consumption and ethylene recovery rate for quasi-plant wide operation optimization of the ethylene column with bottom circulatory system in ethylene complex[J]. Asia-pacific Journal of Chemical Engineering, 2017, 12(5): 694-708. |
35 | Huang D , Luo X L . A novel approach to promptly control product quality in precise distillation columns based on pressure dynamic modeling[J]. Asia-pacific Journal of Chemical Engineering, 2018, 13(4): e2212. |
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