Coke Oven Flue Temperature Control Based on Improved Implicit Generalized Predictive Control
Zhongda Tian†, Shujiang Li, and Yanhong Wang
College of Information Science and Engineering, Shenyang University of Technology
Shenyang, Liaoning 110870, China
The flue temperature of coke oven is an important factor that guarantees the coke yield, the coke quality and the energy consumption of coking production. The heating process of coke oven is an object with multi control variables, nonlinear and large lag. The traditional PID control algorithm cannot further improve the control performance of the coke oven system. An improved implicit generalized predictive control algorithm with better control performance is proposed in this paper. Through inputting control increment value constrained by soft coefficient matrix, the calculation of matrix inversion is avoided. Soft coefficient matrix can reduce the computation time and ensure the rapidity of the system. At the same time, the input weight control law with smoothing filter is used to suppress the overshoot of the system output. Simulation results show that the proposed control method in this paper has the good control performance with faster computation speed. The proposed control method solves the problem of time variation and disturbance of coke oven system. The control algorithm of the coke oven flue temperature in this paper is effective.
-  Q. Yi, M. H. Gong, Y. Huang, Y. H. Hao, J. L. Zhang, and W. Y. Li, “Process Development of Coke Oven Gas to Methanol Integrated with CO2 recycle for Satisfactory Techno-Economic Performance,” Energy, Vol.112, pp. 618-628, 2016.
-  C. H. Yang, M. Wu, D. Y. Shen, and G. Deconinck, “Hybrid Intelligent Control of Gas Collectors of Coke Ovens,” Control Engineering Practice, Vol.9, pp. 725-733, 2001.
-  J. J. Xu, C. Chen, and H. J. Yang, “Temperature Control System for Diode Laser Based on PID Control and Genetic-Algorithm,” J. of Shenyang University of Technology, Vol.39, pp. 449-453, 2017.
-  B. Zhao and H. Li, “Temperature Control of Semi-Conductor Laser with PID Parameter Tuning,” J. of Shenyang University of Technology, Vol.39, pp. 444-448, 2017.
-  Y. N. Guo, D. W. Gong, and J. Cheng, “Coke Oven Heating Temperature Fuzzy Control System,” IEEE Int. Conf. on Control Applications, pp. 195-198, 2004.
-  S. Pang and Y. Y. Lai, “Hybrid Intelligent Control of Coke Oven,” Int. Review on Computers and Software, Vol.6, pp. 1313-1319, 2011.
-  G. F. Li, W. T. Xiao, H. H. Liu, G. Z. Jiang, and J. Liu, “Fuzzy Control of Flue Temperature in Coke Oven Heating Process,” Computer Modelling and New Technologies, Vol.18, pp. 484-489, 2014.
-  G. F. Li, Y. S. Gu, J. Y. Kong, G. Z. Jiang, and L. X. Xie, “Intelligent Control of Coke Oven Air-Fuel Ratio,” Int. Review on Computers and Software, Vol.7, pp. 1262-1267, 2012.
-  G. F. Li, Y. He, G. Z. Jiang, and L. X. Xie, “Research on the Air-Fuel Ratio Intelligent Control Method for Coke Oven Combustion Energy Saving,” 2nd Int. Conf. on Frontiers of Manufacturing and Design Science, pp. 2873-2877, 2012.
-  L. Zhang, Q. Y. Xu, S. B. Jin, and J. N. Li, “Coking Flue Temperature RBF Neural Network Model,” Proc. of the 2015 27th Chinese Control and Decision Conf., pp. 5885-5887, 2015.
-  G. Z. Jiang, T. T. He, G. F. Li, and J. Y. Kong, “Intelligent Control of Coke Oven,” 2010 Int. Conf. on Logistics Systems and Intelligent Management, pp. 512-515, 2010.
-  H. S. Li and J. M. Zhang, “Improved PID Design Using New State Space Predictive Functional Control Optimization Based Structure,” Chemometrics & Intelligent Laboratory Systems, Vol.151, pp. 95-102, 2016.
-  S. Appari, R. Tanaka, C. Y. Li, S. Kudo, J. I. Hayashi, V. M. Janardhanan, 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 J., Vol.266, pp. 82-90, 2015.
-  A. Mozaffari, N. L. Azad, J. K. Hedrick, and A. Taghavipour, “A Hybrid Switching Predictive Controller with Proportional Integral Derivative Gains and GMDH Neural Representation of Automotive Engines for Coldstart Emission Reductions,” Engineering Applications of Artificial Intelligence, Vol.48, pp. 72-94, 2014.
-  R. D. Zhang, A. K. Xue, and F. R. Gao, “Temperature Control of Industrial Coke Furnace Using Novel State Space Model Predictive Control,” IEEE Trans. on Industrial Informatics, Vol.10, pp. 2084-2092, 2014.
-  H. S. Li, H. B. Zhou, and J. M. Zhang, “Dynamic Matrix Control Optimization Based New PIPD Type Control for Outlet Temperature in a Coke Furnace,” Chemometrics & Intelligent Laboratory Systems, Vol.142, pp. 245-254, 2015.
-  S. Wu, R. D. Zhang, R. Q. Lu, and F. R. Gao, “Design of Dynamic Matrix Control Based PID for Residual Oil Outlet Temperature in a Coke Furnace,” Chemometrics & Intelligent Laboratory Systems, Vol.134, pp. 110-117, 2014.
-  Z. D. Tian, X. W. Gao, B. L. Gong, and T. Shi, “Time-Delay Compensation Method for Networked Control System Based on Time-Delay Prediction and Implicit PIGPC,” Int. J. of Automation and Computing, Vol.12, pp. 648-656, 2015.
-  W. J. He, H. T. Zhang, Z. Y. Chen, K. Gao, B. Shan, and R. Chen, “Generalized Predictive Control of Temperature on an Atomic Layer Deposition Reactor,” IEEE Trans. on Control Systems Technology, Vol.23, pp. 2408-2415, 2015.
-  K. Belda and D. Vošmik, “Explicit Generalized Predictive Control of Speed and Position of PMSM Drives,” IEEE Trans. on Industrial Electronics, Vol.63, pp. 3889-3896, 2016.
-  K. Li, D. W. Li, Y. G. Xi, and D. B. Yin, “Model Predictive Control with Feedforward Strategy for Gas Collectors of Coke Ovens,” Chinese J. of Chemical Engineering, Vol.22, pp. 769-773, 2014.
-  L. Deng, Y. Huang, M. R. Fei, M. Zheng, and J. Jiang, “Improved Generalized Predictive Control and its Application in Temperature System,” Chinese J. of Scientific Instrument, Vol.35, pp. 1057-1064, 2014.
-  G. F. Li, P. X. Qu, J. Y. Kong, G. Z. Jiang, L. X. Xie, P. Gao, Z. H. Wu, and Y. He, “Coke Oven Intelligent Integrated Control System,” Applied Mathematics & Information Sciences, Vol.7, pp. 1043-105, 2013.
-  D. W. Clarke and C. Mohtadi, “Properties of Generalized Predictive Control,” Automatica, Vol.25, pp. 859-875, 1989.
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