Optimal Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model

›› 2008, Vol. 16 ›› Issue (2): 235-240.

• SYSTEM ENGINEERING • Previous Articles Next Articles

Optimal Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model

XIONG Zhihua¹, ZHANG Jie²

1. Department of Automation, Tsinghua University, Beijing 100084, China;
2. School of Chemical Engineering and Advanced Materials, University of Newcastle, Newcastle upon Tyne, NE17RU, U. K.;
3. Supply Chain Management&Logistics, IBM China Research Lab, Beijing 100094, China

Received:2006-11-30 Revised:2007-10-28 Online:2008-04-28 Published:2008-04-28
Supported by:
the National Natural Science Foundation of China(60404012,60674064);UK EPSRC(GR/N13319 and GR/R10875);the National High Technology Research and Development Program of China(2007AA04Z193);New Star of Science and Technology of Beijing City(2006A62);IBM China Research Lab 2007 UR-Program

Optimal Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model

熊智华¹, 董进²

1. Department of Automation, Tsinghua University, Beijing 100084, China;
2. School of Chemical Engineering and Advanced Materials, University of Newcastle, Newcastle upon Tyne, NE17RU, U. K.;
3. Supply Chain Management&Logistics, IBM China Research Lab, Beijing 100094, China

通讯作者: XIONG Zhihua,E-mail:zhxiong@tsinghua.edu.cn
基金资助:
the National Natural Science Foundation of China(60404012,60674064);UK EPSRC(GR/N13319 and GR/R10875);the National High Technology Research and Development Program of China(2007AA04Z193);New Star of Science and Technology of Beijing City(2006A62);IBM China Research Lab 2007 UR-Program

Abstract

Abstract: A batch-to-batch optimal iterative learning control(ILC)strategy for the tracking control of product quality in batch processes is presented.The linear time-varying perturbation(LTVP)model is built for product quality around the nominal trajectories.To address problems of model-plant mismatches,model prediction errors in the previous batch run are added to the model predictions for the current batch run.Then tracking error transition models can be built,and the ILC law with direct error feedback is explicitly obtained.A rigorous theorem is proposed,to prove the convergence of tracking error under ILC.The proposed methodology is illustrated on a typical batch reactor and the results show that the performance of trajectory tracking is gradually improved by the ILC.

Key words: iterative learning control, linear time-varying perturbation model, batch process

摘要： A batch-to-batch optimal iterative learning control(ILC)strategy for the tracking control of product quality in batch processes is presented.The linear time-varying perturbation(LTVP)model is built for product quality around the nominal trajectories.To address problems of model-plant mismatches,model prediction errors in the previous batch run are added to the model predictions for the current batch run.Then tracking error transition models can be built,and the ILC law with direct error feedback is explicitly obtained.A rigorous theorem is proposed,to prove the convergence of tracking error under ILC.The proposed methodology is illustrated on a typical batch reactor and the results show that the performance of trajectory tracking is gradually improved by the ILC.

关键词: iterative learning control, linear time-varying perturbation model, batch process

XIONG Zhihua, ZHANG Jie, DONG Jin. Optimal Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model[J]. , 2008, 16(2): 235-240.

熊智华, 董进. Optimal Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model[J]. , 2008, 16(2): 235-240.

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Optimal Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model

Optimal Iterative Learning Control for Batch Processes Based on Linear Time-varying Perturbation Model

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