Fast incremental predictive control with constraints and its application to control of GLCC liquid-level

doi:10.3969/j.issn.0438-1157.2013.03.029

CIESC Journal ›› 2013, Vol. 64 ›› Issue (3): 993-999.DOI: 10.3969/j.issn.0438-1157.2013.03.029

Previous Articles Next Articles

Fast incremental predictive control with constraints and its application to control of GLCC liquid-level

HE Defeng, BAO Rong, ZHENG Kaihua, YU Li

School of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, Zhejiang, China

Received:2012-07-04 Revised:2012-10-21 Online:2013-03-05 Published:2013-03-05
Supported by:
supported by the National Natural Science Foundation of China(60904040),the Specialized Research Fund for Doctoral Program of Higher Education of China(20093317120002)and the Major Specialized Research Projects of Science & Technology of Zhejiang Province(2011C16040).

快速增量约束预测控制及在GLCC液位控制中的应用

何德峰, 鲍荣, 郑凯华, 俞立

浙江工业大学信息工程学院,浙江杭州 310023

通讯作者: 何德峰(1979—),男,博士,副教授。
作者简介:何德峰(1979—),男,博士,副教授。
基金资助:
国家自然科学基金项目(60904040);高等学校博士点专项科研基金项目(20093317120002);浙江省重大科技专项(2011C16040)。

Abstract

Abstract: For liquid-level control problem of gas-liquid cylindrical cyclone(GLCC) multi-phase flow device,an incremental multi-variables model predictive control(MPC) algorithm was proposed.By using state-space models with incremental control and the stair-like strategy,constrained multi-variables MPC was formulated as an optimized control problem.In order to solve the constrained optimization problem,the methods of coordinate alternation and golden section were introduced to calculate online the value of incremental control variables.This led to predictive control actions.Finally,the liquid-level control model with double-inputs and single-output of the GLCC multi-phase flow device was used to illustrate the effectiveness of the algorithm obtained.

Key words: model predictive control, constrained control, GLCC multi-phase flow device, liquid-level control, coordinate alternation method

摘要： 针对气-液柱状旋流式(GLCC)多相流量计的液位控制问题,提出一种增量多变量模型预测控制(MPC)算法。采用控制增量状态空间模型和阶梯式控制策略,建立约束多变量MPC优化控制问题。为在线计算约束优化问题,引入坐标轮换法和黄金分割法,在线计算控制变量增量值,进而得到预测控制量。最后,以GLCC多相流量计的两输入单输出液位控制模型为例,仿真验证本文算法的有效性。

关键词: 模型预测控制, 约束控制, GLCC多相流量计, 液位控制, 坐标轮换法

CLC Number:

TP273

HE Defeng, BAO Rong, ZHENG Kaihua, YU Li. Fast incremental predictive control with constraints and its application to control of GLCC liquid-level[J]. CIESC Journal, 2013, 64(3): 993-999.

何德峰, 鲍荣, 郑凯华, 俞立. 快速增量约束预测控制及在GLCC液位控制中的应用[J]. 化工学报, 2013, 64(3): 993-999.

References 16

[1]	Mohan R,Wang S,Shoham O.Design and performance of passive control system for gas-liquid cylindrical cyclone separators[J].ASME Journal of Energy Resources Technology,1998,120(1):49-55
[2]	Gomez L E,Mohan R S,Marrelli J D,et al.Aspect ratio modeling and design procedure for GLCC compact separators[J].ASME Journal of Energy Resources Technology,1999,121(1):15-23
[3]	Kouba G Chevron,Wang S,et al.Review of the state-of-the-art gas/liquid cylindrical cyclone(GLCC)technology-field applications//Proceedings of the 2006 Society of Petroleum Engineers(SPE)International Oil & Gas Conference.Beijing,China,2006:1-9
[4]	Wang S,Mohan R S,Shoham O,et al.Performance improvement of gas-liquid cylindrical cyclone separators using integrated liquid level and pressure control system//Proceedings of the ASME Energy Sources Technology Conference and Exhibition.New Orlean,France,2000:185-192
[5]	Qin S J,Badgwell T A.A survey of industrial model predictive control technology[J].Control Engineering Practice,2003,11(7):733-764
[6]	Vouzis P D,Bleris G L,Arnold M G,Kothare M V.A system-on-a-chip implementation for embedded real-time model predictive control[J].IEEE Transactions on Control Systems Technology,2009,17(5):1006-1015
[7]	He Defeng(何德峰),Zhou Tao(邹涛),Yu Li(俞立).Receding horizon control for grade transition of large-scale polypropylene production plants[J].CIESC Journal(化工学报),2011,61(2):405-412
[8]	Shin M Y,Primbs J A.A Riccati based interior point algorithm for the computation in constrained stochastic MPC[J].IEEE Transactions on Automatica Control,2012,57(3):760-765
[9]	Richter S,Morari M,Jones C N.Towards computational complexity certification for constrained MPC based on Lagrange relaxation and the fast gradient method//Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference.Orlando,USA,2011:5223-5229
[10]	Li P,Wendt M,Wozny G.A probabilistically constrained model predictive controller[J].Automatica,2002,38(8):1171-1176
[11]	Wang Y,Boyd S.Fast model predictive control using online optimization[J].IEEE Transactions on Control Systems Technology,2010,18(2):267-278
[12]	Liu Youfei(刘有飞),Wu Gang(吴刚),Wei Henghua(魏衡华),Sun Demin(孙德敏).Stair-like dynamic matrix control and its application in temperature control system[J].Journal of University of Science and Technology of China(中国科学技术大学学报),2002,32(3):347-352
[13]	Zheng Tao(郑涛),He Defeng(何德峰),Chen Wei(陈薇),Wu Gang(吴刚).Fast stair-like nonlinear model predictive control algorithm[J].Journal of System Simulation(系统仿真学报),2007,19(22):5206-5209
[14]	Dominguez L F,Pistikopoulos E N.Recent advances on explicit multiparametric nonlinear model predictive control//Proceedings of the International Symposium on New Frontiers in Chemical and Biochemical Engineering.Thessaloniki,Greece,2011:609-619
[15]	Yuan Yaxiang(袁亚湘),Sun Wenyu(孙文瑜).Theory and Methods of Optimization(最优化理论与方法)[M].Beijing:Science Press,2007:103-141
[16]	Chen Baolin(陈宝林).Optimization Theory and Algorithm(最优化理论与算法)[M].Beijing:Tsinghua University Press,2005:132-140

Fast incremental predictive control with constraints and its application to control of GLCC liquid-level

快速增量约束预测控制及在GLCC液位控制中的应用

PDF (PC)

Knowledge

Cited

Abstract

Cite this article

share this article

References 16

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	Jianghuai ZHANG, Zhong ZHAO. Robust minimum covariance constrained control for C₃ hydrogenation process and application [J]. CIESC Journal, 2023, 74(3): 1216-1227.
[2]	Siqi FENG, Xionglin LUO. Online estimation of switching time for a class of optimization-control mode switch of economic model predictive control [J]. CIESC Journal, 2020, 71(S2): 225-240.
[3]	Hongbiao ZHOU, Yu ZHANG, Xiaoying BAI, Baolian LIU, Huanyu ZHAO. Model predictive control of nonlinear system based on adaptive fuzzy neural network [J]. CIESC Journal, 2020, 71(7): 3201-3212.
[4]	Defeng HE, Yongda ZHANG, Lianming LI, Xiang QIU. Lexicographic economic predictive control without terminal constraints for CFBB combustion systems [J]. CIESC Journal, 2020, 71(3): 1210-1216.
[5]	Hongwei GUAN, Lingjian YE, Feifan SHEN, De GU, Zhihuan SONG. Dynamic real-time optimization for gold cyanidation leaching process using economic model predictive control [J]. CIESC Journal, 2020, 71(3): 1122-1130.
[6]	Dejian LI, Haoran LIU, Bin LIU, Zeren LIU, Weitao WANG, Yan WEN. Predictive control of free calcium oxide based on improved echo state network [J]. CIESC Journal, 2019, 70(12): 4749-4759.
[7]	ZHANG Jia, LUO Xionglin, XU Feng, XU Jun. Influence of feed forward variables on feasible region of model predictive control [J]. CIESC Journal, 2016, 67(9): 3776-3783.
[8]	LI Qiumei, TIAN Xuemin, SHANG Linyuan. Detection of model-plant mismatch based on partial correlation analysis of MPC controllers [J]. CIESC Journal, 2016, 67(3): 852-857.
[9]	WANG Yuhong, YANG Pu. Application of a control strategy based on PWA model in CSTR system [J]. CIESC Journal, 2016, 67(3): 865-870.
[10]	PANG Qiang, ZOU Tao, CONG Qiumei. Adaptive MPC method of VCM distillation process by acetylene method based on RELS [J]. CIESC Journal, 2015, 66(2): 662-668.
[11]	FENG Kai, LU Jiangang, CHEN Jinshui. Identification and model predictive control of LPV models based on LS-SVM for MIMO system [J]. CIESC Journal, 2015, 66(1): 197-205.
[12]	JIN Xin, CHI Qinghua, LIU Kangling, LIANG Jun. Disturbance rejection constraints generalized predictive control of diagonal CARIMA model [J]. CIESC Journal, 2014, 65(4): 1310-1316.
[13]	SHANG Linyuan, TIAN Xuemin. Performance diagnosis of MPC control loop based on weighted L₂-Hausdorff subspace distance [J]. CIESC Journal, 2014, 65(11): 4477-4483.
[14]	LUO Xionglin, YU Yang, XU Jun. Online optimization implementation on model predictive control in chemical process [J]. CIESC Journal, 2014, 65(10): 3984-3992.
[15]	LIU Xin，HAO Xiaohong，YANG Xinhua，AN Aimin. Nonlinear model predictive control of the direct internal reforming solid oxide fuel cell system [J]. Chemical Industry and Engineering Progree, 2014, 33(04): 900-906.