Modeling and Parameter Identification of Raw Meal Calcination Process

被引:6
|
作者
Qiao, Jinghui [1 ]
Chai, Tianyou [2 ]
机构
[1] Shenyang Univ Technol, Sch Mech Engn, Shenyang 110870, Peoples R China
[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China
基金
中国国家自然科学基金;
关键词
Calciner temperature; outlet temperature of preheater C1 (i.e; the no. 1 preheater); raw meal calcination process; T-S fuzzy model; IMPLEMENTATION; CALCINER; SYSTEMS; FLOW;
D O I
10.1109/TMECH.2014.2332256
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Raw meal calcination system is a complex mechanical and electrical integration system. This system is different from the traditional machining process without a chemical reaction. Moreover, raw meal calcination in calciner is a complex physical-chemical process, and its dynamic characteristics were rarely researched. In order to verify the rationality of the mechanical structure designed, the dynamic characteristics of the rawmeal calcination system need to be analyzed in advance. Therefore, a mathematical model of this process is being called for. The most important variables to be controlled are the calciner temperature and the outlet temperature of preheater C1 (i.e., the no. 1 preheater). Because of the big time constant associated with thermal dynamic characteristics, controlling the two variables is a thorny problem. This paper presents a modeling and parameter identification procedure for a raw meal calcination process. In addition, a parameter identification method based on the T-S fuzzy model and radial basis function was proposed because the specific heat capacity of pulverized coal particles, rawmeal, and exhaust cannot be measured. The performance index of parameter identification is to minimize the difference of force response between the simulation and the experiment. Finally, both modeling and parameter identification methods were validated by comparing the results of simulation and experiments.
引用
收藏
页码:1204 / 1217
页数:14
相关论文
共 50 条
  • [1] Conditions Identification Model Based on LLNFM and RBR in Cement Raw Meal Calcination Process
    Qiao, Jinghui
    Chai, Tianyou
    26TH CHINESE CONTROL AND DECISION CONFERENCE (2014 CCDC), 2014, : 2804 - 2809
  • [2] Intelligent Switching Control for Cement Raw Meal Calcination Process
    Qiao, Jinghui
    Chai, Tianyou
    PROCEEDINGS OF THE 10TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA 2012), 2012, : 280 - 285
  • [3] Soft Measurement Model of Raw Meal Decomposition Ratio Based on Data Driven for Raw Meal Calcination Process
    Qiao, Jinghui
    Zhao, Xiaowei
    Chai, Tianyou
    PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC), 2019, : 2857 - 2862
  • [4] Soft measurement model and its application in raw meal calcination process
    Qiao, Jinghui
    Chai, Tianyou
    JOURNAL OF PROCESS CONTROL, 2012, 22 (01) : 344 - 351
  • [5] An Intelligent Temperature Switching Control for Cement Raw Meal Calcination Process
    Qiao, Jinghui
    Zhang, Handi
    Chai, Tianyou
    2013 10TH IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION (ICCA), 2013, : 804 - 809
  • [6] Quality Index Modeling Based on Mechanism and Multirate Sampled-data in Cement Raw Meal Calcination Process
    Qiao, Jinghui
    Chai, Tianyou
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 1 - 6
  • [7] KINETICS OF CALCINATION IN CEMENT RAW MEAL NODULES
    BAPAT, JD
    VISVESVARAYA, HC
    RAO, TR
    RAO, DS
    ZEMENT-KALK-GIPS, 1994, 47 (03): : 156 - 160
  • [8] RMDR Optimal Setting Based on Multi-model for Raw Meal Calcination Process
    Qiao, Jinghui
    Chai, Tianyou
    PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017), 2017, : 4494 - 4499
  • [9] Intelligence-Based Temperature Switching Control for Cement Raw Meal Calcination Process
    Qiao, Jinghui
    Chai, Tianyou
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2015, 23 (02) : 644 - 661
  • [10] Intelligent Setting Control of Raw Meal Calcination Proces
    Qiao, Jinghui
    Chai, Tianyou
    Wang, Hong
    2011 50TH IEEE CONFERENCE ON DECISION AND CONTROL AND EUROPEAN CONTROL CONFERENCE (CDC-ECC), 2011, : 7659 - 7664