Temperature control of an acrylonitrile polymerization kettle using multiple models with second level adaptation

doi:10.16511/j.cnki.qhdxxb.2016.24.023

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Abstract A generalized predictive control method was developed from multiple models with second level adaptation for temperature control the acrylonitrile polymerization process which has long time delays and large parameter uncertainties. Several adaptive models are designed for the system parameter ranges with the parameters estimated by a recursive least squares algorithm. Then, the model weights are calculated based on the parameter estimates and the prediction error of each model. Then, the parameter estimates are used as the true values of the parameters to determine the control action via the generalized predictive control algorithm. Simulation results show that this method enables a system with unknown parameters to quickly converge to the true value. The system performance of the system and the tracking accuracy of the ideal temperature are significantly improved compared with conventional multiple model adaptive control.

Keywords multiple models second level adaptation generalized predictive control polymerization kettle adaptive control

ZTFLH:

TP273

Issue Date: 15 July 2016

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	WANG Zhenlei
	MAO Fuxing
	WANG Xin

Cite this article:

WANG Zhenlei,MAO Fuxing,WANG Xin. Temperature control of an acrylonitrile polymerization kettle using multiple models with second level adaptation[J]. Journal of Tsinghua University(Science and Technology), 2016, 56(7): 707-716.

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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2016.24.023 OR http://jst.tsinghuajournals.com/EN/Y2016/V56/I7/707

[1] Chan K, Bui T N N, Woo Y Y. Fabrications and electrochemical properties of two-phase activated carbon nanofibers from electrospinning[C]//Proceedings of the IEEE Nanotechnology Materials and Devices Conference. Gyeongju, South Korea:IEEE Nanotechnology Council, 2005:412-413.
[2] 丁东湖, 金建祥. 聚氯乙烯温度控制方案的设计及应用[J]. 化工自动化及仪表, 2004, 31(2):15-16.DING Donghu, JIN Jianxiang. A study on application and control strategies of PVC temperature system[J]. Control and Instruments in Chemical Industry, 2004, 31(2):15-16.(in Chinese).
[3] Nemtoi G, Onu N A. Thermal effect of some polymerization and polycondensation reactions[J]. Ploymeric Ammonium Quaternary Salts. European Ploymer Journal, 2000, 36(12):2679-2680.
[4] YE Yanfei, WANG Bailin, SHAO Mingheng, et al. Improved generalized predictive control in polymerization process[C]//Proceedings of the Second International Conference on Mechanic Automation and Control Engineering. Huhehaote:Inner Mongolia University of Technology, 2011:1354-1357.
[5] SUN Zhou, GUO Liji. Modeling and fuzzy controller design for ACR Polymerizing-Kettles[C]//Proceedings of the 8th IEEE International Conference on Control and Automation. Xiamen:IEEE Control System Society, 2010:1688-1693.
[6] Jalili-Kharaajoo M. Predictive control of a continuous stirred tank reactor based on neuro-fuzzy model of the process[C]//Proceedings of the SICE Annual Conference. Fukui, Japan:The Society of Instrument and Control Engineers, 2003:3277-3282.
[7] Morse A S. Supervisory control of families of linear set-point controllers:Part I. Exact matching[J]. IEEE Transactions on Automatic Control, 1996, 41(10):1413-1431.
[8] Narendra K, Balakrishnan S. Adaptive control using multiple models[J]. IEEE Transactions on Automatic Control, 1997, 42(2):171-187.
[9] ZHUO Han, Narendra K S. New concepts in adaptive control using multiple models[J]. IEEE Transactions on Automatic Control, 2012, 42(1):171-187.
[10] Narendra K S, ZHUO Han. Discrete-time adaptive control using multiple models[C]//Proceedings of the American Control Conference. San Francisco, USA:American Automatic Control Council, 2011:2921-2926.
[11] Pandey V K, Ka I, Mahanta C. Multiple models and second level adaptation for a class of nonlinear systems with nonlinear parameterization[C]//Proceedings of the 9th International Conference on Industrial and Information Systems. Gwalior, India:ABV-Indian Institute of Information Technology and Management, 2014:1-6.
[12] Narendra K S, ZHUO Han. The changing face of adaptive control:The use of multiple models[J]. Annual Review in Control, 2011, 35(1):1-12.
[13] ZHUO Han, Narendra K S. Second level adaptation using multiple models[C]//Proceedings of the American Control Conference. San Francisco, USA:American Automatic Control Council, 2011:2350-2355.
[14] 唐振波. 丙烯腈水相沉淀聚合生产工艺研究[J]. 应用化工, 2011, 40(6):1069-1072. TANG Zhenbo. Research on productive process of precipitation polymerization of acrylonitrilein water phase[J]. Applied Chemical Industry, 2011, 40(6):1069-1072.(in Chinese)
[15] 刘忠涛, 基于LMI的丙烯腈聚合釜温度控制问题研究[D]. 哈尔滨:哈尔滨工业大学, 2010.LIU Zhongtao. Research on Control of the Acrylonitrile Polymerization Reactor Temperature Based on LMI[D]. Harbin:Harbin Institute of Technology, 2010.(in Chinese).
[16] DING Yongsheng, KUANG Xiaoliang, HAO Rong, et al. An intelligent cooperative decoupling controller for coagulation bath in polyacrylonitrile carbon fiber production[J]. IEEE Transactions on Control Systems Technology, 2013, 21(2):467-479.
[17] Narendra K S, Driolle O A. Adaptive control using multiple models, switching, and tuning[J]. International Journal of Adaptive Control and Signal Processing, 2003, 17(2):87-102.
[18] Narendra K S, CHENG Xiang. Adaptive control of discrete-time system using multiple models[J]. IEEE Transactions on Automatic Control, 2000, 45(9):1669-1686.
[19] 席裕庚. 预测控制[M]. 北京:国防工业出版社, 1993.XI Yugeng. Predictive Control[M]. Beijing:National Defense Industry Press, 1993.(in Chinese).
[20] 李小田, 王昕, 王振雷, 等. 一种基于多模型切换的阶梯式广义预测控制算法[J]. 化工学报, 2012, 63(1):193-196.LI Xiaotian, WANG Xin, WANG Zhenlei, et al. A stair-like generalized predictive control algorithm based on multiple models switching[J]. CIESC Journal, 2012, 63(1):193-196.(in Chinese).