DocumentCode :
3550836
Title :
An integrated batch-to-batch iterative learning control and within batch control strategy for batch processes
Author :
Xiong, Zhihua ; Zhang, Jie ; Wang, Xiong ; Xu, Yongmao
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
fYear :
2005
fDate :
8-10 June 2005
Firstpage :
1935
Abstract :
An integrated batch-to-batch iterative learning control (ILC) and within batch on-line shrinking horizon model predictive control (SHMPC) strategy for the tracking control of product qualities in batch processes is proposed. ILC is used for batch-to-batch control based on a batch-wise linear time-varying (LTV) perturbation model and the convergence of batch-wise tracking error under ILC is guaranteed. On-line SHMPC within a batch can reduce the effects of disturbances immediately and improve the performance of the current batch run. The on-line model prediction can be also obtained based on the batch-wise LTV model. The integrated control strategy can complement both methods to obtain good performance of tracking control. The proposed strategy is illustrated on a simulated batch polymerization process.
Keywords :
adaptive control; batch processing (industrial); iterative methods; learning systems; predictive control; time-varying systems; batch control strategy; batch processes; batch-wise linear time-varying perturbation model; integrated batch-to-batch iterative learning control; online model prediction; shrinking horizon model predictive control; simulated batch polymerization process; tracking control; Automatic control; Automation; Chemical engineering; Error correction; Least squares approximation; Linear regression; Noise measurement; Predictive models; Process control; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2005. Proceedings of the 2005
ISSN :
0743-1619
Print_ISBN :
0-7803-9098-9
Electronic_ISBN :
0743-1619
Type :
conf
DOI :
10.1109/ACC.2005.1470252
Filename :
1470252
Link To Document :
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