# American Institute of Mathematical Sciences

December  2015, 8(6): 1223-1237. doi: 10.3934/dcdss.2015.8.1223

## Intelligent control model and its simulation of flue temperature in coke oven

 1 College of Machinery and Automation, Wuhan University of Science and Technology, Wuhan 430081, China, China, China 2 Intelligent Systems and Biomedical Robotics Group, School of Computing, University of Portsmouth, Portsmouth PO1 3HE, United Kingdom, United Kingdom, United Kingdom

Received  May 2015 Revised  September 2015 Published  December 2015

In this paper, one-variable linear regression mathematical model of top of regenerator temperature and flue temperature in machine side is built using the linear regress theory. The parameters of ARX model is determined by identification method of least square method and the mathematical model of flue temperature control is established. Applying the basis cascade control theory, system adopts flue temperature and coal flue gas flow as controlled parameters of host circuit and subsidiary circuit respectively. The compound Fuzzy-PID control strategy is presented combined with the characteristics of temperature system after analyzing the conventional PID control algorithm and fuzzy control algorithm. Using step signal and periodic signal to simulate the conventional PID and compound Fuzzy-PID algorithm, the result has indicated: Compound Fuzzy PID control algorithm combines with the advantages of fuzzy control and PID control algorithm, including fast response speed and strong anti-interference ability. When external conditions change, the fuzzy PID compound control can show the strong adaptability and robustness which effectively improve the stability of the control system.
Citation: Gongfa Li, Wei Miao, Guozhang Jiang, Yinfeng Fang, Zhaojie Ju, Honghai Liu. Intelligent control model and its simulation of flue temperature in coke oven. Discrete and Continuous Dynamical Systems - S, 2015, 8 (6) : 1223-1237. doi: 10.3934/dcdss.2015.8.1223
##### References:
 [1] S. Appari, R. Tanaka, C. Y. Li, S. Kudo, J. Hayashi, M. J. Vinod, H. Watanabe and K. Norinaga, Predicting the temperature and reactant concentration profiles of reacting flow in the partial oxidation of hot coke oven gas using detailed chemistry and a one-dimensional flow model, Chemical Engineering Journal, 266 (2015), 82-90. doi: 10.1016/j.cej.2014.12.041. [2] W. H. Chen, M. R. Lin, T. S. Leu and S. W. Du, An evaluation of hydrogen production from the perspective of using blast furnace gas and coke oven gas as feedstock, International Journal of Hydrogen Energy, 36 (2011), 11727-11737. doi: 10.1016/j.ijhydene.2011.06.049. [3] S. K. Das, K. M. Godiwalla and S. P. Mehrotra, A mathematical model for prediction of physical properties of the coke oven charge during carbonization, High Temperature Materials and Processe, 26 (2007), 43-57. [4] R. Fabbri, R. Johnson, S. Novo and C. Núñez, On linear-quadratic dissipative control processes with time-varying coefficients, Discrete and Continuous Dynamical Systems - Series S (DCDS-S), 33 (2013), 193-210. doi: 10.3934/dcds.2013.33.193. [5] X. W. Gao and Y. P. Zhao, The fuzzy adaptive PID in the simulation of coke oven temperature control, Journal of Northeastern University, 27 (2006), 1067-1070. [6] Y. N. Guo, D. W. Gong and J. Cheng, Coke oven heating temperature fuzzy control system, in Proceedings of the IEEE International Conference on Control Applications, 2004, 195-198. [7] D. R. Jenkins and M. R. Mahoney, Programmed heating of coke ovens for increased coke size, Ironmaking and Steelmaking, 37 (2010), 570-577. doi: 10.1179/030192310X12706364542948. [8] G. Z. Jiang, T. T. He, G. F. Li and J. Y. Kong, Intelligent control of coke oven, in Proceedings of International Conference on Logistics Systems and Intelligent Management, Vol 1, IEEE, 2010, 512-515. doi: 10.1109/ICLSIM.2010.5461371. [9] J. L. Karst, E. Petit and J. P. Gaillet, Optimization of coke oven charging by use of a mathematical model, Revue de Metallurgie. Cahiers D'Informations Techniques, 101 (2004), 447-452. doi: 10.1051/metal:2004186. [10] E. T. Ko, S. K. Hwang and J. S. Lee, A combustion control modeling of coke oven by swarm-based fuzzy system, in Proceedings of SICE-ICASE International Joint Conferenc, 2006, 2503-2507. doi: 10.1109/SICE.2006.314682. [11] Q. Lei, J. Y. Li, M. Wu and Y. He, The application of multi-objective differential evolution algorithm in the combustion process of coke oven, in Proceedings of the 32nd Chinese Control Conference, 2013, 8395-8400. [12] Q. Lei and M. Wu, Fuzzy optimization control of the temperature for the heating process in coke oven based on co-evolution, in Proceedings of the 26th Chinese Control Conference, 2007, 420-424. [13] Q. Lei, M. Wu, W. H. Cao and S. Y. Hou, An intelligent integrated method for soft-sensing of the flue temperature in coke oven and its application, Journal of East China University of Science and Technology (Natural Science Edition), 32 (2013), 726-766. [14] G. F. Li, Y. S. Gu, J. Y. Kong, G. Z. Jiang and L. X. Xie, Intelligent diagnosis of coke oven heating production, Sensors and Transducers, 16 (2012), 226-232. [15] G. F. Li, Y. He, G. Z. Jiang, J. Y. Kong and L. X. Xie, Research on the air-fuel ratio intelligent control method for coke oven combustion energy saving, in Proceedings of 2nd International Conference on Frontiers of Manufacturing and Design Science, 2011, 2873-2877. doi: 10.4028/www.scientific.net/AMM.121-126.2873. [16] G. F. Li, P. X. Qu, J. Y. Kong, G. Z. Jiang, L. X. Xie, P. Gao, Z. H. Gao and Y. He, Coke oven intelligent integrated control system, Applied Mathematics and Information Sciences, 7 (2013), 1043-1050. [17] G. F. Li, W. T. Xiao, G. Z. Jiang, J. Y. Kong, J. Liu, Y. K. Zhang and F. W. Cheng, Soft-sensing model of coke oven flue temperature, Sensors and Transducers, 161 (2013), 265-270. [18] G. F. Li, Y. S. Gu, J. Y. Kong, G. Z. Jiang and L. X. Xie, Intelligent control of coke oven air-fuel ratio, International Review on Computers and Software, 7 (2012), 1262-1267. [19] G. F. Li, J. Y. Kong, G. Z. Jiang, L. X. Xie, Z. G. Jiang and G. Zhao, Air-fuel ratio intelligent control in coke oven combustion process, INFORMATION-An International Interdisciplinary Journal, 15 (2012), 4487-4494. [20] W. Lin, Y. H. Feng and X. X. Zhang, Numerical study of volatiles production, fluid flow and heat transfer in coke ovens, Applied Thermal Engineerin, 81 (2015), 353-358. doi: 10.1016/j.applthermaleng.2015.02.056. [21] W. S. Lin, L. Zhang and A. Z. Gu, Effects of hydrogen content on nitrogen expansion liquefaction process of coke oven gas, Cryogenics, 61 (2014), 149-153. doi: 10.1016/j.cryogenics.2014.01.006. [22] Q. Lü and E. Zuazua, Robust null controllability for heat equations with unknown switching control mode, Discrete and Continuous Dynamical Systems - Series S (DCDS-S), 34 (2014), 4183-4210. doi: 10.3934/dcds.2014.34.4183. [23] G. Nicolas and V. R. Tatiana, Prediction of coke oven wall pressure, Fuel, 139 (2015), 692-703. [24] K. P. Prachethan, A. Kinlekar, K. Mallikarjuna and M. Ranjan, Coal pyrolysis and kinetic model for nonrecovery coke ovens, Ironmaking and Steelmaking, 38 (2011), 608-612. [25] R. Razzaq, C. S. Li and S. J. Zhang, Coke oven gas: Availability, properties, purification and utilization in china, Fuel, 113 (2013), 287-299. doi: 10.1016/j.fuel.2013.05.070. [26] D. L. Russell, Control via decoupling of a class of second order linear hybrid systems, Discrete and Continuous Dynamical Systems - Series S (DCDS-S), 7 (2014), 1321-1334. doi: 10.3934/dcdss.2014.7.1321. [27] G. Sergei and M. Yuri, A simple non-linear model of immune response, Chaos, 16 (2013), 125-132. doi: 10.1016/S0960-0779(02)00232-1. [28] K. Tsuda, Reduction in coke oven heat consumption through improved fuel valve adjustment, in Proceedings of IFAC Workshop on Automation in the Mining, Mineral and Metal Industries, 2012, 132-133. [29] H. T. Wang, W. J. Yang, J. H. Zhou, Z. H. Wang, J. Z. Liu and K. F. Cen, Calculation and analysis on evaporation and mixing characteristics of droplets in high temperature flue, Journal of Zhejiang University (Engineering Science), 45 (2011), 878-884. [30] W. Wang, M. Wu, W. H. Cao and Q. Le, Fuzzy-expert control based on combination grey prediction model for flue temperature in coke oven, Control and Decision, 25 (2010), 185-190. [31] M. Wu, Q. Lei and W. H. Cao, Flue temperature fuzzy control for coke oven heating process based on multi-operative modes analysis, Journal of Central South University (Science and Technology), 39 (2008), 155-161. [32] M. Wu, Q. Lei, W. H. Cao and J. H. She, Integrated soft sensing of coke-oven temperature, Control Engineering Practice, 19 (2011), 1116-1125. doi: 10.1016/j.conengprac.2011.06.001. [33] M. Wu, Y. X. Liu, W. H. Cao and Q. Lei, Research and application of intelligent optimization control system for coke oven heating combustion process, Journal of metallurgical automatio, 30 (2006), 25-28. [34] W. T. Xiao, G. F. Li, H. H. Liu, G. Z. Jiang, Z. Liu, D. S. Chen, W. L. Ding, W. Miao and Z. Li, Soft sensor system of coke oven flue temperature based on CBR and PCA-RBFNN, Computer Modelling and New Technologies, 18 (2014), 951-958. [35] Z. L. Zhang, B. Q. Lin, G. M. Li and Q. Ye, Coke oven gas explosion suppression, Safety Sciencel, 55 (2013), 81-87. doi: 10.1016/j.ssci.2012.12.006. [36] J. Y. Zhang, X. H. Zhang, Z. Chen and L. Li, Thermodynamic and kinetic model of reforming coke-oven gas with steam, Energy, 35 (2010), 3103-3108. doi: 10.1016/j.energy.2010.03.050. [37] M. D. Zheng and F. Q. Ning, Research on coke oven heating control system, Journal of Dalian University Technology, 41 (2001), 442-445.

show all references

##### References:
 [1] S. Appari, R. Tanaka, C. Y. Li, S. Kudo, J. Hayashi, M. J. Vinod, H. Watanabe and K. Norinaga, Predicting the temperature and reactant concentration profiles of reacting flow in the partial oxidation of hot coke oven gas using detailed chemistry and a one-dimensional flow model, Chemical Engineering Journal, 266 (2015), 82-90. doi: 10.1016/j.cej.2014.12.041. [2] W. H. Chen, M. R. Lin, T. S. Leu and S. W. Du, An evaluation of hydrogen production from the perspective of using blast furnace gas and coke oven gas as feedstock, International Journal of Hydrogen Energy, 36 (2011), 11727-11737. doi: 10.1016/j.ijhydene.2011.06.049. [3] S. K. Das, K. M. Godiwalla and S. P. Mehrotra, A mathematical model for prediction of physical properties of the coke oven charge during carbonization, High Temperature Materials and Processe, 26 (2007), 43-57. [4] R. Fabbri, R. Johnson, S. Novo and C. Núñez, On linear-quadratic dissipative control processes with time-varying coefficients, Discrete and Continuous Dynamical Systems - Series S (DCDS-S), 33 (2013), 193-210. doi: 10.3934/dcds.2013.33.193. [5] X. W. Gao and Y. P. Zhao, The fuzzy adaptive PID in the simulation of coke oven temperature control, Journal of Northeastern University, 27 (2006), 1067-1070. [6] Y. N. Guo, D. W. Gong and J. Cheng, Coke oven heating temperature fuzzy control system, in Proceedings of the IEEE International Conference on Control Applications, 2004, 195-198. [7] D. R. Jenkins and M. R. Mahoney, Programmed heating of coke ovens for increased coke size, Ironmaking and Steelmaking, 37 (2010), 570-577. doi: 10.1179/030192310X12706364542948. [8] G. Z. Jiang, T. T. He, G. F. Li and J. Y. Kong, Intelligent control of coke oven, in Proceedings of International Conference on Logistics Systems and Intelligent Management, Vol 1, IEEE, 2010, 512-515. doi: 10.1109/ICLSIM.2010.5461371. [9] J. L. Karst, E. Petit and J. P. Gaillet, Optimization of coke oven charging by use of a mathematical model, Revue de Metallurgie. Cahiers D'Informations Techniques, 101 (2004), 447-452. doi: 10.1051/metal:2004186. [10] E. T. Ko, S. K. Hwang and J. S. Lee, A combustion control modeling of coke oven by swarm-based fuzzy system, in Proceedings of SICE-ICASE International Joint Conferenc, 2006, 2503-2507. doi: 10.1109/SICE.2006.314682. [11] Q. Lei, J. Y. Li, M. Wu and Y. He, The application of multi-objective differential evolution algorithm in the combustion process of coke oven, in Proceedings of the 32nd Chinese Control Conference, 2013, 8395-8400. [12] Q. Lei and M. Wu, Fuzzy optimization control of the temperature for the heating process in coke oven based on co-evolution, in Proceedings of the 26th Chinese Control Conference, 2007, 420-424. [13] Q. Lei, M. Wu, W. H. Cao and S. Y. Hou, An intelligent integrated method for soft-sensing of the flue temperature in coke oven and its application, Journal of East China University of Science and Technology (Natural Science Edition), 32 (2013), 726-766. [14] G. F. Li, Y. S. Gu, J. Y. Kong, G. Z. Jiang and L. X. Xie, Intelligent diagnosis of coke oven heating production, Sensors and Transducers, 16 (2012), 226-232. [15] G. F. Li, Y. He, G. Z. Jiang, J. Y. Kong and L. X. Xie, Research on the air-fuel ratio intelligent control method for coke oven combustion energy saving, in Proceedings of 2nd International Conference on Frontiers of Manufacturing and Design Science, 2011, 2873-2877. doi: 10.4028/www.scientific.net/AMM.121-126.2873. [16] G. F. Li, P. X. Qu, J. Y. Kong, G. Z. Jiang, L. X. Xie, P. Gao, Z. H. Gao and Y. He, Coke oven intelligent integrated control system, Applied Mathematics and Information Sciences, 7 (2013), 1043-1050. [17] G. F. Li, W. T. Xiao, G. Z. Jiang, J. Y. Kong, J. Liu, Y. K. Zhang and F. W. Cheng, Soft-sensing model of coke oven flue temperature, Sensors and Transducers, 161 (2013), 265-270. [18] G. F. Li, Y. S. Gu, J. Y. Kong, G. Z. Jiang and L. X. Xie, Intelligent control of coke oven air-fuel ratio, International Review on Computers and Software, 7 (2012), 1262-1267. [19] G. F. Li, J. Y. Kong, G. Z. Jiang, L. X. Xie, Z. G. Jiang and G. Zhao, Air-fuel ratio intelligent control in coke oven combustion process, INFORMATION-An International Interdisciplinary Journal, 15 (2012), 4487-4494. [20] W. Lin, Y. H. Feng and X. X. Zhang, Numerical study of volatiles production, fluid flow and heat transfer in coke ovens, Applied Thermal Engineerin, 81 (2015), 353-358. doi: 10.1016/j.applthermaleng.2015.02.056. [21] W. S. Lin, L. Zhang and A. Z. Gu, Effects of hydrogen content on nitrogen expansion liquefaction process of coke oven gas, Cryogenics, 61 (2014), 149-153. doi: 10.1016/j.cryogenics.2014.01.006. [22] Q. Lü and E. Zuazua, Robust null controllability for heat equations with unknown switching control mode, Discrete and Continuous Dynamical Systems - Series S (DCDS-S), 34 (2014), 4183-4210. doi: 10.3934/dcds.2014.34.4183. [23] G. Nicolas and V. R. Tatiana, Prediction of coke oven wall pressure, Fuel, 139 (2015), 692-703. [24] K. P. Prachethan, A. Kinlekar, K. Mallikarjuna and M. Ranjan, Coal pyrolysis and kinetic model for nonrecovery coke ovens, Ironmaking and Steelmaking, 38 (2011), 608-612. [25] R. Razzaq, C. S. Li and S. J. Zhang, Coke oven gas: Availability, properties, purification and utilization in china, Fuel, 113 (2013), 287-299. doi: 10.1016/j.fuel.2013.05.070. [26] D. L. Russell, Control via decoupling of a class of second order linear hybrid systems, Discrete and Continuous Dynamical Systems - Series S (DCDS-S), 7 (2014), 1321-1334. doi: 10.3934/dcdss.2014.7.1321. [27] G. Sergei and M. Yuri, A simple non-linear model of immune response, Chaos, 16 (2013), 125-132. doi: 10.1016/S0960-0779(02)00232-1. [28] K. Tsuda, Reduction in coke oven heat consumption through improved fuel valve adjustment, in Proceedings of IFAC Workshop on Automation in the Mining, Mineral and Metal Industries, 2012, 132-133. [29] H. T. Wang, W. J. Yang, J. H. Zhou, Z. H. Wang, J. Z. Liu and K. F. Cen, Calculation and analysis on evaporation and mixing characteristics of droplets in high temperature flue, Journal of Zhejiang University (Engineering Science), 45 (2011), 878-884. [30] W. Wang, M. Wu, W. H. Cao and Q. Le, Fuzzy-expert control based on combination grey prediction model for flue temperature in coke oven, Control and Decision, 25 (2010), 185-190. [31] M. Wu, Q. Lei and W. H. Cao, Flue temperature fuzzy control for coke oven heating process based on multi-operative modes analysis, Journal of Central South University (Science and Technology), 39 (2008), 155-161. [32] M. Wu, Q. Lei, W. H. Cao and J. H. She, Integrated soft sensing of coke-oven temperature, Control Engineering Practice, 19 (2011), 1116-1125. doi: 10.1016/j.conengprac.2011.06.001. [33] M. Wu, Y. X. Liu, W. H. Cao and Q. Lei, Research and application of intelligent optimization control system for coke oven heating combustion process, Journal of metallurgical automatio, 30 (2006), 25-28. [34] W. T. Xiao, G. F. Li, H. H. Liu, G. Z. Jiang, Z. Liu, D. S. Chen, W. L. Ding, W. Miao and Z. Li, Soft sensor system of coke oven flue temperature based on CBR and PCA-RBFNN, Computer Modelling and New Technologies, 18 (2014), 951-958. [35] Z. L. Zhang, B. Q. Lin, G. M. Li and Q. Ye, Coke oven gas explosion suppression, Safety Sciencel, 55 (2013), 81-87. doi: 10.1016/j.ssci.2012.12.006. [36] J. Y. Zhang, X. H. Zhang, Z. Chen and L. Li, Thermodynamic and kinetic model of reforming coke-oven gas with steam, Energy, 35 (2010), 3103-3108. doi: 10.1016/j.energy.2010.03.050. [37] M. D. Zheng and F. Q. Ning, Research on coke oven heating control system, Journal of Dalian University Technology, 41 (2001), 442-445.
 [1] Hong Niu, Zhijiang Feng, Qijin Xiao, Yajun Zhang. A PID control method based on optimal control strategy. Numerical Algebra, Control and Optimization, 2021, 11 (1) : 117-126. doi: 10.3934/naco.2020019 [2] Simone Fiori, Italo Cervigni, Mattia Ippoliti, Claudio Menotta. Synchronization of dynamical systems on Riemannian manifolds by an extended PID-type control theory: Numerical evaluation. Discrete and Continuous Dynamical Systems - B, 2022  doi: 10.3934/dcdsb.2022047 [3] Bin Li, Kok Lay Teo, Cheng-Chew Lim, Guang Ren Duan. An optimal PID controller design for nonlinear constrained optimal control problems. Discrete and Continuous Dynamical Systems - B, 2011, 16 (4) : 1101-1117. doi: 10.3934/dcdsb.2011.16.1101 [4] Bin Li, Xiaolong Guo, Xiaodong Zeng, Songyi Dian, Minhua Guo. An optimal pid tuning method for a single-link manipulator based on the control parametrization technique. Discrete and Continuous Dynamical Systems - S, 2020, 13 (6) : 1813-1823. doi: 10.3934/dcdss.2020107 [5] Tayel Dabbous. Adaptive control of nonlinear systems using fuzzy systems. Journal of Industrial and Management Optimization, 2010, 6 (4) : 861-880. doi: 10.3934/jimo.2010.6.861 [6] Carmen Chicone, Stephen J. Lombardo, David G. Retzloff. Modeling, approximation, and time optimal temperature control for binder removal from ceramics. Discrete and Continuous Dynamical Systems - B, 2022, 27 (1) : 103-140. doi: 10.3934/dcdsb.2021034 [7] Antonio Fernández, Pedro L. García. Regular discretizations in optimal control theory. Journal of Geometric Mechanics, 2013, 5 (4) : 415-432. doi: 10.3934/jgm.2013.5.415 [8] K. Renee Fister, Jennifer Hughes Donnelly. Immunotherapy: An Optimal Control Theory Approach. Mathematical Biosciences & Engineering, 2005, 2 (3) : 499-510. doi: 10.3934/mbe.2005.2.499 [9] H. W. J. Lee, Y. C. E. Lee, Kar Hung Wong. Differential equation approximation and enhancing control method for finding the PID gain of a quarter-car suspension model with state-dependent ODE. Journal of Industrial and Management Optimization, 2020, 16 (5) : 2305-2330. doi: 10.3934/jimo.2019055 [10] Yong Zhao, Qishao Lu. Periodic oscillations in a class of fuzzy neural networks under impulsive control. Conference Publications, 2011, 2011 (Special) : 1457-1466. doi: 10.3934/proc.2011.2011.1457 [11] Omid S. Fard, Javad Soolaki, Delfim F. M. Torres. A necessary condition of Pontryagin type for fuzzy fractional optimal control problems. Discrete and Continuous Dynamical Systems - S, 2018, 11 (1) : 59-76. doi: 10.3934/dcdss.2018004 [12] Aliki D. Muradova, Georgios K. Tairidis, Georgios E. Stavroulakis. Adaptive Neuro-Fuzzy vibration control of a smart plate. Numerical Algebra, Control and Optimization, 2017, 7 (3) : 251-271. doi: 10.3934/naco.2017017 [13] Peng Cheng, Yanqing Liu, Yanyan Yin, Song Wang, Feng Pan. Fuzzy event-triggered disturbance rejection control of nonlinear systems. Journal of Industrial and Management Optimization, 2021, 17 (6) : 3297-3307. doi: 10.3934/jimo.2020119 [14] Brahim Allal, Abdelkarim Hajjaj, Lahcen Maniar, Jawad Salhi. Null controllability for singular cascade systems of $n$-coupled degenerate parabolic equations by one control force. Evolution Equations and Control Theory, 2021, 10 (3) : 545-573. doi: 10.3934/eect.2020080 [15] K.F.C. Yiu, K.L. Mak, K. L. Teo. Airfoil design via optimal control theory. Journal of Industrial and Management Optimization, 2005, 1 (1) : 133-148. doi: 10.3934/jimo.2005.1.133 [16] Gunog Seo, Gail S. K. Wolkowicz. Pest control by generalist parasitoids: A bifurcation theory approach. Discrete and Continuous Dynamical Systems - S, 2020, 13 (11) : 3157-3187. doi: 10.3934/dcdss.2020163 [17] Debra Lewis. Modeling student engagement using optimal control theory. Journal of Geometric Mechanics, 2022, 14 (1) : 131-150. doi: 10.3934/jgm.2021032 [18] Purnima Pandit. Fuzzy system of linear equations. Conference Publications, 2013, 2013 (special) : 619-627. doi: 10.3934/proc.2013.2013.619 [19] Diana Keller. Optimal control of a linear stochastic Schrödinger equation. Conference Publications, 2013, 2013 (special) : 437-446. doi: 10.3934/proc.2013.2013.437 [20] Magdi S. Mahmoud, Mohammed M. Hussain. Control design of linear systems with saturating actuators: A survey. Numerical Algebra, Control and Optimization, 2012, 2 (2) : 413-435. doi: 10.3934/naco.2012.2.413

2021 Impact Factor: 1.865