Title :
Integrated Tracking Control for Batch Processes in the Presence of Model Uncertainties
Author :
Xiong, Zhihua ; Zhang, Jie
Author_Institution :
Tsinghua Univ., Beijing
fDate :
May 30 2007-June 1 2007
Abstract :
An integrated control strategy is proposed to track product quality trajectories of batch processes by updating a linear time-varying perturbation (LTVP) model. To address the problem of model uncertainties, the LTVP model is renewed by using recursive forgetting factor algorithm. Then batch-to-batch iterative learning control (ILC) can be feasibly combined with on-line model predictive control (MPC) within a batch. The integrated strategy can complement both methods to obtain good performance of tracking control. The proposed strategy is demonstrated on a simulated batch reactor.
Keywords :
batch processing (industrial); iterative methods; learning systems; predictive control; self-adjusting systems; time-varying systems; batch processes; batch reactor; batch-to-batch iterative learning control; integrated control strategy; integrated tracking control; linear time-varying perturbation model; model predictive control; model uncertainties; product quality trajectories; recursive forgetting factor algorithm; Automatic control; Automation; Centralized control; Chemical engineering; Impurities; Inductors; Predictive control; Predictive models; Process control; Uncertainty;
Conference_Titel :
Control and Automation, 2007. ICCA 2007. IEEE International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4244-0818-4
Electronic_ISBN :
978-1-4244-0818-4
DOI :
10.1109/ICCA.2007.4376796