Simultaneous optimization and control for polypropylene grade transition with two-layer hierarchical structure

doi:10.1016/j.cjche.2015.08.025

Chinese Journal of Chemical Engineering ›› 2015, Vol. 23 ›› Issue (12): 2053-5064.DOI: 10.1016/j.cjche.2015.08.025

• 第25届中国过程控制会议专栏 • 上一篇下一篇

Simultaneous optimization and control for polypropylene grade transition with two-layer hierarchical structure

Haichuan Lou^1,2, Hongye Su¹, Yong Gu¹, Lei Xie¹, Gang Rong¹, Weifeng Hou²

1 Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China;
2 Zhejiang Supcon Software Co., Ltd., Hangzhou 310053, China

收稿日期:2015-05-25 修回日期:2015-07-26 出版日期:2015-12-28 发布日期:2016-01-19
通讯作者: Hongye Su
基金资助:
Supported by the Electronic Information Industry Development Foundation of China (20140806) and the National Natural Science Foundation of China (61374121,61134007).

Simultaneous optimization and control for polypropylene grade transition with two-layer hierarchical structure

Haichuan Lou^1,2, Hongye Su¹, Yong Gu¹, Lei Xie¹, Gang Rong¹, Weifeng Hou²

1 Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China;
2 Zhejiang Supcon Software Co., Ltd., Hangzhou 310053, China

Received:2015-05-25 Revised:2015-07-26 Online:2015-12-28 Published:2016-01-19
Contact: Hongye Su
Supported by:
Supported by the Electronic Information Industry Development Foundation of China (20140806) and the National Natural Science Foundation of China (61374121,61134007).

摘要/Abstract

摘要： In this paper, a two-layer hierarchical structure of optimization and control for polypropylene grade transition was raised to overcome process uncertain disturbances that led to the large deviation between the open-loop reference trajectory and the actual process. In the upper layer, the variant time scale based control vector parametric methods (VTS-CVP) was used for dynamic optimization of transition reference trajectory, while nonlinear model predictive controller (NMPC) based on closed-loop subspace and piece-wise linear (SSARX-PWL) model in the lower layer was tracking to the reference trajectory from the upper layer for overcoming high-frequency disturbances. Besides, mechanism about trajectory deviation detection and optimal trajectory updating onlinewere introduced to ensure a smooth transition for the entire process. The proposed method was validated with the real data from an industrial double-loop propylene polymerization reaction process with developed dynamic mechanismmathematicalmodel.

关键词: Polypropylene, Grade transition, Two-layer hierarchical structure, Deviation detection

Abstract: In this paper, a two-layer hierarchical structure of optimization and control for polypropylene grade transition was raised to overcome process uncertain disturbances that led to the large deviation between the open-loop reference trajectory and the actual process. In the upper layer, the variant time scale based control vector parametric methods (VTS-CVP) was used for dynamic optimization of transition reference trajectory, while nonlinear model predictive controller (NMPC) based on closed-loop subspace and piece-wise linear (SSARX-PWL) model in the lower layer was tracking to the reference trajectory from the upper layer for overcoming high-frequency disturbances. Besides, mechanism about trajectory deviation detection and optimal trajectory updating onlinewere introduced to ensure a smooth transition for the entire process. The proposed method was validated with the real data from an industrial double-loop propylene polymerization reaction process with developed dynamic mechanismmathematicalmodel.

Key words: Polypropylene, Grade transition, Two-layer hierarchical structure, Deviation detection

Haichuan Lou, Hongye Su, Yong Gu, Lei Xie, Gang Rong, Weifeng Hou. Simultaneous optimization and control for polypropylene grade transition with two-layer hierarchical structure[J]. Chinese Journal of Chemical Engineering, 2015, 23(12): 2053-5064.

参考文献

[1] H.C. Lou, H.Y. Su, L. Xie, Y. Gu, G. Rong, Inferential model for industrial polypropylene melt index prediction with embedded priori knowledge and delay estimation, Ind. Eng. Chem. Res. 51 (25) (2012) 8510-8525.

[2] Y. Wang, H. Seki, S. Ohyama, K. Akamatsu, M. Ogawa, M. Ohshima, Optimal grade transition control for polymerization reactors, Comput. Chem. Eng. 24 (2-7) (2000) 1555-1561.

[3] M.R. Rahimpour, J. Fathikalajahi, B. Moghtaderi, A.N. Farahani, A grade transition strategy for the prevention ofmelting and agglomeration of particles in an ethylene polymerization reactor, Chem. Eng. Technol. 28 (7) (2005) 831-841.

[4] J. Zhuge, M.G. Ierapetritou, Integration of scheduling and control with closed loop implementation, Ind. Eng. Chem. Res. 51 (2013) 8550-8565.

[5] L.D. Mark, M. Nikolaou, J. Jones, D. Nicholson, RTO: An overview and assessment of current practice, J. Process Control 21 (6) (2011) 874-884.

[6] Y. Chu, F. You, Integration of scheduling and control with online closed-loop implementation: Fast computational strategy and large-scale global optimization algorithm, Comput. Chem. Eng. 47 (20) (2013) 248-268.

[7] P. Tatjewski, Advanced control and on-line process optimization in multilayer structures, Annu. Rev. Control. 32 (1) (2008) 71-85.

[8] S. Engell, Feedback control for optimal process operation, J. Process Control 17 (3) (2007) 203-219.

[9] A. Zanin,M.T. Gouvea, D. Odloak, Industrial implementation of a real-time optimization strategy for maximizing production of LPG in a FCC unit, Comput. Chem. Eng. 24 (2-7) (2010) 525-531.

[10] V.M. Zavala, L.T. Biegler, The advanced-step NMPC controller: Optimality, stability and robustness, Automatica 45 (1) (2009) 86-93.

[11] L. Biegler, V. Zavala, Large-scale nonlinear programming using IPOPT: An integrating framework for enterprise-wide dynamic optimization, Comput. Chem. Eng. 33 (3) (2009) 575-582.

[12] G. Dnnebier, D.V. Hessem, J.V. Kadam, K.U. Klat, M. Schlegel, Optimization and control of polymerization processes, Chem. Eng. Technol. 28 (2005) 575-580.

[13] A. Flores-Tlacuahuac, L.T. Biegler, Integrated control and process design during optimal polymer grade transition operations, Comput. Chem. Eng. 32 (11) (2008) 2823-2837.

[14] M.A.-h Ali, Optimal grade transition control for liquid-propylene polymerization reactor, Asian J. Control 12 (2010) 413-425.

[15] L. Würth, R. Hannemann, W. Marquardt, A two-layer architecture for economically optimal process control and operation, J. Process Control 21 (3) (2011) 311-321.

[16] L.T. Biegler, An overview of simultaneous strategies for dynamic optimization, Chem. Eng. Process. 46 (11) (2007) 1043-1053.

[17] K.L. Teo, Control parametrization enhancing transform to optimal control problems, Nonlinear Anal. 63 (2005) 2223-2236.

[18] R. Loxton, K. Teo, V. Rehbock, Optimal control problems with multiple characteristic time points in the objective and constraints, Automatica 44 (11) (2008) 2923-2929.

[19] Y.Q. Hu, X.G. Liu, A.K. Xue, An improved control vector iteration approach for nonlinear dynamic optimization, Chin. J. Chem. Eng. 22 (2) (2014) 141-145.

[20] F. Sun, W.M. Zhong, H. Cheng, F. Qian, Novel control vector parameterization method with differential evolution algorithm and its application in dynamic optimization of chemical processes, Chin. J. Chem. Eng. 21 (1) (2013) 64-71.

[21] A. Wchter, L.T. Biegler, On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming, Math. Program. 106 (2006) 25-57.

[22] L. Aguirre, M. Coelho, M. Corrêa, On the interpretation and practice of dynamical differences between Hammerstein and Wiener models, Control Theory A 152 (4) (2005) 349-356.

[23] M. Jansson, A new subspace identification method for open and closed loop data, Proceedings of the 16th IFAC World Congress, Czech Republic 2005, pp. 372-378.

[24] P. Julian, A High Level Canonical Piecewise Linear Representation: Theory and Applications(Ph.D.Thesis) Universidad Nacional del Sur, Bahia Blanca, Argentina, 1999.

[25] J.L. Figueroa, A.C. Desages, Use of piecewise linear approximations for steady state back off analysis, Optim. Control. Appl. Meth. 19 (2) (1998) 93-110.

[26] P. Kadlec, R. Grbi, B. Gabrys, Review of adaptation mechanisms for data-driven soft sensors, Comput. Chem. Eng. 35 (1) (2011) 1-24.

[27] J.J. Zacca, W.H. Ray, Modelling of the liquid phase polymerization of olefins in loop reactors, Chem. Eng. Sci. 48 (22) (1993) 3743-3765.

[28] A.S. Reginato, J.J. Zacca, A.R. Secchi, Modeling and simulation polymerization in nonideal loop reactors, AICHE J. 49 (10) (2003) 2642-2654.

Simultaneous optimization and control for polypropylene grade transition with two-layer hierarchical structure

Simultaneous optimization and control for polypropylene grade transition with two-layer hierarchical structure

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	Zhenqiang Zhang, Danfeng Yu, Xiubin Xu, Huayi Li, Taoyan Mao, Cheng Zheng, Jianjia Huang, Hui Yang, Zihan Niu, Xu Wu. A polypropylene melt-blown strategy for the facile and efficient membrane separation of oil-water mixtures[J]. 中国化学工程学报, 2021, 29(1): 383-390.
[2]	Zhensheng Yang, Zheng Sun, Dongsheng Cui, Pingli Li, Zhiying Wang. TIPS behavior for IPP/nano-SiO₂ blend membrane formation and its contribution to membrane morphology and performance[J]. Chinese Journal of Chemical Engineering, 2019, 27(2): 467-475.
[3]	Xiaojuan Jia, Zexian Low, He Chen, Sen Xiong, Yong Wang. Atomic layer deposition of Al₂O₃ on porous polypropylene hollow fibers for enhanced membrane performances[J]. Chinese Journal of Chemical Engineering, 2018, 26(4): 695-700.
[4]	Hongyan Shen, Youzhi Liu. One-step synthesis of hydrophobic magnesium hydroxide nanoparticles and their application in flame-retardant polypropylene composites[J]. Chinese Journal of Chemical Engineering, 2018, 26(10): 2199-2205.
[5]	Yesid Tapiero, Julio Sánchez, Bernabé L. Rivas. Interpenetrating polymers supported on microporous polypropylene membranes for the transport of chromium ions[J]. , 2017, 25(7): 938-946.
[6]	Sen Xiong, Ting Sheng, Liang Kong, Zhaoxiang Zhong, Jun Huang, Yong Wang. Enhanced performances of polypropylene membranes by molecular layer deposition of polyimide[J]. , 2016, 24(7): 843-849.
[7]	Zhenhao Xi, Jie Chen, Tao Liu, Ling Zhao, Lih-Sheng Turng. Experiment and simulation of foaming injection molding of polypropylene/nano-calcium carbonate composites by supercritical carbon dioxide[J]. Chinese Journal of Chemical Engineering, 2016, 24(1): 180-189.
[8]	周蓉, 狄玲, 王苍, 方艳, 吴健, 徐志康. Surface Functionalization of Microporous Polypropylene Membrane with Polyols for Removal of Boron Acid from Aqueous Solution[J]. Chinese Journal of Chemical Engineering, 2014, 22(1): 11-18.
[9]	费正顺, 胡斌, 叶鲁彬, 梁军. ARX-NNPLS Model Based Optimization Strategy and Its Application in Polymer Grade Transition Process^*[J]. Chinese Journal of Chemical Engineering, 2012, 20(5): 971-979.
[10]	赵众, 马楠楠, 潘立登, 徐宁, 孙康. Direct Adaptive Control Based on Gradient Estimation[J]. , 2008, 16(5): 752-761.
[11]	苏磊, 吴学华, 刘秀茹, 陈丽英, 陈克宇, 洪时明. 升温升压过程对聚丙烯在超临界水中降解的影响[J]. , 2007, 15(5): 738-741.
[12]	成怀刚, 王世昌. 充碳塑料管壳式增湿-去湿淡化装置及过程：模拟和实验研究[J]. , 2007, 15(4): 478-485.
[13]	熊丽, 梁军, 钱积新. 基于主元分析和核密度估计的多变量统计过程监控及在工厂聚丙烯催化剂反应器的应用[J]. , 2007, 15(4): 524-532.
[14]	刘亚青, 赵贵哲. 三聚氯化磷腈微胶囊阻燃剂/聚丙烯复合材料的性能研究[J]. , 2007, 15(3): 429-432.
[15]	申屠宝卿, 李继鹏, 翁志学. 油酸修饰纳米CaCO3对PP结晶行为和力学性能的影响[J]. , 2006, 14(6): 814-818.