IMC-based iterative learning control for batch processes with uncertain time delay

被引:97
作者
Liu, Tao [1 ]
Gao, Furong [1 ]
Wang, Youqing [2 ]
机构
[1] Hong Kong Univ Sci & Technol, Dept Chem & Biomol Engn, Kowloon, Hong Kong, Peoples R China
[2] Univ Calif Santa Barbara, Dept Chem Engn, Santa Barbara, CA 93106 USA
关键词
Batch process; Uncertain time delay; Internal model control (IMC); Iterative learning control (ILC); Convergence; MODEL-PREDICTIVE CONTROL; QUADRATIC OPTIMAL-CONTROL; CONTROL SCHEMES; FEEDBACK; SYSTEMS; DESIGN; FREQUENCY; TRACKING;
D O I
10.1016/j.jprocont.2009.10.008
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Based on the Internal model control (IMC) structure, an iterative learning control (ILC) scheme is proposed for batch processes with model uncertainties including time delay mismatch An important merit is that the IMC design for the initial run of the proposed control scheme is independent of the Subsequent ILC for realization of perfect tracking Sufficient conditions to guarantee the convergence of ILC are derived. To facilitate the controller design. a unified controller form is proposed for implementation of both IMC and ILC in the proposed control scheme Robust tuning constraints of the Unified controller are derived in terms of the process uncertainties described ill a Multiplicative form To deal with process uncertainties, the unified controller call be monotonically tuned to meet the compromise between tracking performance and control system robust stability Illustrative examples from the recent literature are performed to demonstrate the effectiveness and merits of the proposed control scheme (C) 2009 Elsevier Ltd All rights reserved.
引用
收藏
页码:173 / 180
页数:8
相关论文
共 35 条
[1]   Iterative learning control: Brief survey and categorization [J].
Ahn, Hyo-Sung ;
Chen, YangQuan ;
Moore, Kevin L. .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, 2007, 37 (06) :1099-1121
[2]  
[Anonymous], 1989, ROBUST PROCESS CONTR
[3]   Control and optimization of batch processes [J].
Bonvin, Dominique ;
Srinivasan, Bala ;
Hunkeler, David .
IEEE CONTROL SYSTEMS MAGAZINE, 2006, 26 (06) :34-45
[4]   Iterative learning control for a non-minimum phase plant based on a reference shift algorithm [J].
Cai, Zhonglun ;
Freeman, Chris T. ;
Lewin, Paul L. ;
Rogers, Eric .
CONTROL ENGINEERING PRACTICE, 2008, 16 (06) :633-643
[5]   Performance assessment for iterative learning control of batch units [J].
Chen, Junghui ;
Kong, Cho-Kai .
JOURNAL OF PROCESS CONTROL, 2009, 19 (06) :1043-1053
[6]  
Chin I, 2004, AUTOMATICA, V40, P1913, DOI [10.1016/j.automatica.2004.05.011, 10.1016/j.automatica.2004.05.012]
[7]   Iterative learning dual-mode control of exothermic batch reactors [J].
Cho, Wonhui ;
Edgar, Thomas F. ;
Lee, Jietae .
CONTROL ENGINEERING PRACTICE, 2008, 16 (10) :1244-1249
[8]   Robust iterative learning control with current feedback for uncertain linear systems [J].
Doh, TY ;
Moon, JH ;
Jin, KB ;
Chung, MJ .
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 1999, 30 (01) :39-47
[9]   Loop shaping for iterative control of batch processes [J].
Gorinevsky, D .
IEEE CONTROL SYSTEMS MAGAZINE, 2002, 22 (06) :55-65
[10]   Iterative learning control design for Smith predictor [J].
Hu, QP ;
Xu, JX ;
Lee, TH .
SYSTEMS & CONTROL LETTERS, 2001, 44 (03) :201-210