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水泥生料预分解过程智能优化设定控制 被引量:2

Intelligent optimal-setting control for cement raw meal pre-calcining process
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摘要 在生料预分解过程中,由于生料边界条件频繁变化,致使产品的质量指标生料分解率过低或过高,从而增加了回转窑的负荷或导致最低一级旋风筒下料管堵塞.为了解决上述问题,本文提出了一个智能优化设定方法,由回路预设定模块、分解率预报模块、前馈补偿模块、反馈补偿模块组成.这个方法能够根据生料边界条件的变化在线调整控制回路的设定值.所提出的方法已经成功应用于酒钢宏达水泥生料预分解过程,取得了显著的应用效果.工业应用表明所提出的智能优化设定方法能够将生料分解率稳定在工艺范围内. In the pre-calcining process of raw meal,boundary conditions of raw meal(i.e.,flow,ingredients and particle size) are varying frequently;the decomposition rate of raw meal(RMDR) cannot be kept in the desirable ranges.This causes the declination of the production rate per hour and the blockage in the lower feeding tubes.To solve this problem,we propose an intelligent setting-control system in which the set-points of control loops are adjusted online according to the variations of the boundary conditions of raw meal.This system consists of four modules: a control-loop pre-setting module,a feedback compensation module based on the fuzzy rules,a feedforward compensation module based on the fuzzy rules and a soft measurement module for RMDR.This method has been successfully applied to the pre-calcining process the raw meal of Jiuganghongda Cement Plant in China and its efficiency has been validated by the practical application results.Industrial applications show that the proposed intelligent optimization method maintains the rate of decomposition of raw material in processes within a stable range.
出处 《控制理论与应用》 EI CAS CSCD 北大核心 2011年第11期1534-1540,共7页 Control Theory & Applications
基金 国家重点基础研究发展计划资助项目(2009CB320601) 国家自然科学基金资助项目(61020106003) 高等学校学科创新引智计划资助项目(B08015) 教育部科学技术研究重大资助项目(308007)
关键词 分解炉 预热器 生料预分解过程 智能优化设定 生料分解率 calciner preheater pre-calcining process of raw meal intelligent optimal-setting decomposition rate of raw meal
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参考文献9

  • 1MAKAREMI I, FATEHI A, ARAABI B N, et al. Abnormal condi- tion detection in a cement rotary kiln with system identification meth- ods[J]. Journal of Process Control, 2009, 19(9): 1538 - 1545.
  • 2ILIUTA I, JOHANSEN K D, JENSEN L S. Mathematical model- ing of an in-line low-NOx ealciner[J]. Chemical Engineering Science, 2002, 57(5): 805 - 820.
  • 3KOUMBOULIS F N, KOUVAKAS N D. Indirect adaptive neural control for precalcination in cement plants[J]. Mathematics and Com- puters in Simulation, 2002, 60(5): 325 - 334.
  • 4柴天佑,丁进良,王宏,苏春翌.复杂工业过程运行的混合智能优化控制方法[J].自动化学报,2008,34(5):505-515. 被引量:85
  • 5QIAO J H, CHAI T Y. Soft measurement model and its applica- tion in raw calcination process[J]. Journal of Process Control, 2011, doi: 10.1016/j.jprocont.2011.08.005.
  • 6ARSHADI N, JURISICA I. Data mining for case-based reasoning in high-dimensional biological domains[J], IEEE Transactions on Knowledge and Data Engineering, 2005, 17(8): 1127 - 1137.
  • 7谭明皓,柴天佑.基于案例推理的层流冷却过程建模[J].控制理论与应用,2005,22(2):248-253. 被引量:24
  • 8CHIU S L. Fuzzy model identification based on cluster estimation[J]. Journal of lnteUigent and Fuzzy Systems, 1994, 2(3): 267 - 278.
  • 9MOUDGAL V G, PASSINO K M, YURKOVICH S. Rule-based con- trol for a flexible-link robot[J]. IEEE Transactions on Control Sys- tems Technology, 1994, 2(4): 392 - 405.

二级参考文献34

  • 1王笑波,任德祥,邵惠鹤,柴天佑.一种多层次递阶建模方法[J].系统仿真学报,2001,13(z1):18-20. 被引量:6
  • 2谭明皓,柴天佑.基于案例推理的层流冷却过程建模[J].控制理论与应用,2005,22(2):248-253. 被引量:24
  • 3严爱军,柴天佑,岳恒.竖炉焙烧过程的多变量智能优化控制[J].自动化学报,2006,32(4):636-640. 被引量:20
  • 4单旭沂.宝钢2050mm热轧层流冷却控制系统改造开发[C]..杭州: 中国科技年会[C].,1999..
  • 5王仲初 柴天佑.基于模型的中厚板水幕连续冷却的前馈-反馈控制系统.自动化学报,2000,26(8):163-167.
  • 6CHAI Tianyou, TAN Minghao, CHEN Xiaoyan, et al. Intelligent optimization control for laminar cooling [C] // Proc of the 15th IFAC World Congress. Barcelona, Spain: Elsevier Science,2002.
  • 7AUMAN P M, GRIFFITHS D K, HILL D R. Hot strip mill nm-out table temperature control [ J]. Iron and Steel Engineer, 1967,44(9):174- 179.
  • 8GROCH A G,GUBERNAT R,BIRSTEIN E R.Automatic control of laminar flow cooling in continuous and reversing hot strip mills [ J].Iron and Steel Engineer, 1990,67(9): 16 - 20.
  • 9MOFFAT R W, MOORE M C, ROBINSON M J, et al. Computer control of hot strip coiling temperature with variable flow laminar spray [C]//AISE Year Book. Pittsburgh: [ s. n. ], 1985:474 - 481.
  • 10LEITHOLF M D, D AHM J R. Model reference control of runout table cooling at LTV [C]//AISE Year Book. Pittsburgh: [ s. n. ], 1989:255 - 259.

共引文献106

同被引文献20

  • 1YAN A, CHAI T, YU W, et al. Multi-objective evaluation-based hy- brid intelligent control optimization for shaft furnace roasting pro- cess [J]. Control Engineering Practice, 2012, 20(9): 857 - 868.
  • 2CHAI T, WU F, DING J, et al. Intelligent work-situation fault diagno- sis and fault-tolerant system for the shaft-furnace roasting process [J]. Proceedings of the Institution of Mechanical Engineers, Part L" Jour- nal of Systems and Control Engineering, 2007, 221(6): 843 - 855.
  • 3CHAI T, DING J, WU F. Hybrid intelligent control for optimal oper- ation of shaft furnace roasting process [J]. Control Engineering Prac- tice, 2011, 19 (3): 264 - 275.
  • 4CHAI T, ZHAO L, QIU J, et al. Integrated network-based model pre- dictive control for setpoints compensation in industrial processes [J]. IEEE Transactions on Industrial lnformatics, 2013, 9(1): 417 - 426.
  • 5DIRKSZ D A, SCHERPEN J M A. Power-based setpoint control: ex- perimental results on a planar manipulator [J]. IEEE Transactions on Control Systems Technology, 2012, 20(5): 1384 - 1391.
  • 6HERNANDEZ-DEL-OLMO F, GAUDIOSO E, NEVADO A. Au- tonomous adaptive and active tuning up of the dissolved oxygen setpoint in a wastewater treatment plant using reinforcement learn- ing [J]. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 2012, 42(5): 768 - 774.
  • 7GUERRERO J, GUISASOLA A, VILANOVA R, el al. Improving the performance of a WWTP control system by model-based setpoint op-timization [J]. Environmental Modelling and Software, 2011, 26(4): 492 - 497.
  • 8WANG W, LI H X, ZHANG J T. A hybrid approach for supervi- sory control of furnace temperature [J]. Control Engineering Prac- tice, 2003, 11(11): 1325 - 1334.
  • 9AMODT A, PLAZA E. Case-based reasoning: foundational issues, methodological variations, and system approaches [J]. AI Communi- cations, 1994, 7(1): 39 - 59.
  • 10LUO B, CUI Q, WANG H, et al. Optimal joint water-filling for co- ordinated transmission over frequency-selective fading channels [J]. IEEE Communications Letters, 2011, 15(2): 190 - 192.

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