Szczegóły

Tytuł artykułu

Simulation and Analysis of Sintering Furnace Temperature Based on Fuzzy Neural Network Control

Tytuł czasopisma

Archives of Foundry Engineering

Rocznik

2021

Wolumin

vo. 21

Numer

No 1

Afiliacje

Chaoxin, Zou : Guizhou Normal University, China ; Rong, Li : Guizhou Normal University, China ; Zhiping, Xie : Guizhou Normal University, China ; Ming, Su : Guizhou Normal University, China ; Jingshi, Zeng : Guizhou Zhenhua New Material Co., Ltd., China ; Xu, Ji : Guizhou Normal University, China ; Xiaoli, Ye : Guizhou Normal University, China ; Ye, Wang : Guizhou Normal University, China

Autorzy

Słowa kluczowe

Fuzzy neural network ; Furnace temperature control ; PID

Wydział PAN

Nauki Techniczne

Zakres

23-30

Wydawca

The Katowice Branch of the Polish Academy of Sciences

Bibliografia

[1] Li, H.S., Miao, Q. & Zhou, R.M. (2014). Research on control algorithm of ceramic kiln temperature control system. Journal of Wuhan University of Technology. 36(10), 135-139. DOI: 10.3963/j.issn.1671-4431.2014.10.024.
[2] Zhu, D.Q. & Jiang, K.R. (2009). Design and simulation of fuzzy neural network controller for drying process. Journal of System Simulation. 21(15), 4768-4771. DOI: 10.16182/j.cnki.joss.2009.15.079.
[3] Zhang, Z.M., Zhang, J.Y. & Feng, X.G. (2019). Design of hot blast stove temperature control system based on RBF neural network tuning. Journal of Hebei University of Science and Technology. 40(06), 503-511. DOI: 10.7535/hbkd.2019yx06007.
[4] Bai, G.Z. & Yu, J.H. (2016). PID parameter self-tuning based on improved fuzzy neural network. Computer Application Research. 33(11), 3358-3363+3368. DOI: 10.3969/j.issn.1001-3695.2016.11.035.
[5] Li, C.L. & Huang, C.Z. (2010). Design of temperature control system based on fuzzy neural network. Microcomputer Information. 26(07), 75-76+98. DOI: 10.3969/j.issn.2095-6835.2010.07.031.
[6] Li, G.Q., Tong, S.H. & Lu, L.X. (2013). Analysis of the temperature field in a continuous sintering furnace for solar cells. Computer Simulation. 30(01), 188-192+218. DOI: 10.3969/j.issn.1006-9348.2013.01.043.
[7] Huang, B., Xie, G.J., Liang, W.S. & Zhang, J.W. (2018). Application of heating furnace temperature control system based on hybrid fuzzy PID. Electric Drive. 48(02), 43-46. DOI: 10.19457/j.1001-2095.20180208.
[8] Zhou, G.L., Peng, Y.F. & Dong, H.S. (2007). Design of adaptive fuzzy PID controller based on T-S model. Industrial Instrumentation and Automation. 2, 22-25. DOI: CNKI: SUN: GYZD.0.2007-02-005.
[9] Tan, M., Cheng, C.H. & Lu, C. (2006). Research on the temperature control system of vacuum sintering furnace based on neural network. Measurement and Control Technology. 2, 31-32+53. DOI: 10.19708/j.ckjs.2006.02.010.
[10] Wang, J.P. & Ku, M.S. (2010). Application of FNN on atmospheric heating furnace of distillation unit. Computer Measurement and Control. 18(11), 2649-2651. DOI: 10.16526/j.cnki.11-4762/tp.2010.11.003. [11] Chen, B.F., Yin, P.L. & Ma, L. (2010). Research on temperature control system based on fuzzy neural network. Computer and Digital Engineering. 38(07), 54-57. DOI: 10.3969/j.issn.1672-9722.2010.07.016.
[12] Li, M.H. & Li, Z.Q. (2012). Research on Decoupling Control Strategy of Injection Molding Machine Barrel Temperature Based on Neural Network. Ceramics. 4, 17-19. DOI: 10.19397/j.cnki.ceramics.2012.04.004.
[13] Hu, Y.N. & Ma, W.M. (2017). Research and application of paper quantitative moisture control strategy based on FNN decoupling. China Paper. 36(07), 48-53. DOI: 10.11980/j.issn.0254-508X.2017.07.009. [14] Zhang, L., Zhang, J.C., Han, H.G. & Qiao, J.F. (2020). Process control of biochemical phosphorus removal in sewage treatment based on fuzzy neural network. CIESC Journal. 71(03). 1217-1225. DOI: 10.11949/0438-1157.20191514.
[15] Tao, X.M., Luo, L. & Liu, Z.G. (2015). Research and simulation of injection molding machine barrel temperature control algorithm based on segmented PID. Plastics. 44(03), 68-70. DOI: CNKI: SUN: SULA.0.2015-03-022.
[16] Zhou, P.Q. (2016). Research on synchronization control technology of double winches based on fuzzy neural network. Machine Design and Manufacture. 9, 64-68. DOI: 10.19356/j.cnki.1001-3997.2016.09.017.
[17] Li, J.J., Xu, Y., Zhang, G., Wei, Z.Y. & Zhang, Y.B. (2015). Irrigation controller design based on BP neural network prediction and fuzzy control. Machine Design and Research. 31(05), 150-154. DOI: 10.13952/j.cnki.jofmdr. 2015.0207.
[18] Luo, C.N., Hao, R.K. & Yang, W. (2018). Boiler temperature control simulation in industrial production process. Computer simulation. 35(09), 358-362. DOI: 10.3969/j.issn.1006-9348.2018.09.074.
[19] Zhao, J. & Xu, H. (2016). Computer simulation study on segmental control of barrel temperature of injection molding machine. Synthetic Resin and Plastics. 33(05), 61-63. DOI: 10.3969/j.issn.1002-1396.2016.05.018.

Data

2021.02.12

Typ

Article

Identyfikator

DOI: 10.24425/afe.2021.136074 ; ISSN 2299-2944

Źródło

Archives of Foundry Engineering; 2021; vo. 21; No 1; 23-30
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