Integrated Batch-to-Batch Iterative Learning Control and within Batch Control of Product Quality for Batch Processes
| Authors: | Xiong Zhihua, Tsinghua University, China, China
Zhang Jie, University of Newcastle, Newcastle upon Tyne, UK, United Kingdom
Wang Xiong, Tsinghua University, China, China
Xu Yongmao, Tsinghua University, China, China |
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| Topic: | 6.1 Chemical Process Control |
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| Session: | Advances in Process Control |
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| Keywords: | Batch-to-batch control, Iterative learning control, Shrinking horizon, Model predictive control, Batch processes |
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Abstract
An integrated strategy for the tracking control of product qualities in batch processes is proposed by combing batch-to-batch iterative learning control (ILC) with on-line shrinking horizon model predictive control (SHMPC) within a batch. ILC is used in batch-to-batch control 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 integrated control strategy can complement both strategies to obtain good performance of tracking trajectories. The proposed strategy is illustrated on a simulated batch polymerization process. The results demonstrate that the performance of tracking product qualities can be improved quite well under the integrated control strategy than under the simple batch-to-batch ILC, especially when disturbances exist.
