Optimal iterative learning control for end-point product qualities in semi-batch process based on neural network model

被引：0
作者：
ZhiHua Xiong
Jin Dong
Jie Zhang
机构：
[1] Tsinghua University,Department of Automation
[2] IBM China Research Lab,Supply Chain Management & Logistics
[3] University of Newcastle,School of Chemical Engineering and Advanced Materials
来源：
Science in China Series F: Information Sciences | 2009年 / 52卷
关键词：
iterative learning control; neural network; semi-batch process; product quality;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
An optimal iterative learning control (ILC) strategy of improving endpoint products in semi-batch processes is presented by combining a neural network model. Control affine feed-forward neural network (CAFNN) is proposed to build a model of semi-batch process. The main advantage of CAFNN is to obtain analytically its gradient of endpoint products with respect to input. Therefore, an optimal ILC law with direct error feedback is obtained explicitly, and the convergence of tracking error can be analyzed theoretically. It has been proved that the tracking errors may converge to small values. The proposed modeling and control strategy is illustrated on a simulated isothermal semi-batch reactor, and the results show that the endpoint products can be improved gradually from batch to batch.
引用
收藏
页码：1136 / 1144
页数：8
相关论文
共 38 条
[1]  
Bonvin D.(1998)Optimal operation of batch reactors—A personal view J Process Contr 8 355-368
[2]  
Park S.(1988)Optimal production of secreted protein in fed-batch reactors AIChE J 34 1550-1558
[3]  
Ramirez W. F.(2006)A survey of iterative learning control IEEE Contr Syst Mag 26 96-114
[4]  
Bristow D. A.(2007)Iterative learning control applied to batch processes: an overview Contr Eng Pract 15 1306-1318
[5]  
Tharayil M.(2005)Iterative learning control—An optimization paradigm Ann Rev Contr 29 57-70
[6]  
Alleyne A. G.(1996)Iterative learning control for discrete-time system with exponential rate of convergence IEE Proc D -Contr Theor Appl 143 217-224
[7]  
Lee J. H.(2000)Model-based iterative learning control with a quadratic criterion for time-varying linear systems Automatica 36 641-657
[8]  
Lee K. S.(2003)Iterative learning control-based batch process control technique for integrated control of end product properties and transient profiles of process variables J Process Contr 13 607-621
[9]  
Owens D. H.(2003)Product quality trajectory tracking of batch processes using iterative learning control based on time varying perturbation model Ind Eng Chem Res 42 6802-6814
[10]  
Hatonen J.(2004)A reliable neural network model based optimal control strategy for a batch polymerisation reactor Ind Eng Chem Res 43 1030-1038
1234