Run-to-run product quality control of batch processes |
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Authors: | Li Jia Ji-ping Shi Da-shuai Cheng Min-sen Chiu |
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Institution: | 1. Shanghai Key Laboratory of Power Station Automation Technology,School of Mechatronics Engineering and Automation,Shanghai University,Shanghai 200072,P.R.China 2. Faculty of Engineering,National University of Singapore,Singapore |
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Abstract: | Batch processes have been increasingly used in the production of low volume and high value added products. Consequently, optimization
control in batch processes is crucial in order to derive the maximum benefit. In this paper, a run-to-run product quality
control based on iterative learning optimization control is developed. Moreover, a rigorous theorem is proposed and proven
in this paper, which states that the tracking error under the optimal iterative learning control (ILC) law can converge to
zero. In this paper, a typical nonlinear batch continuous stirred tank reactor (CSTR) is considered, and the results show
that the performance of trajectory tracking is gradually improved by the ILC.
Project supported by the Science Foundation of Shanghai Municipal Education Commission (Grant No.09Y208), and the Science
Foundation of Science and Technology Commission of Shanghai Municipality (Grant Nos.08DZ2272400, 09DZ2273400) and the “11th
Five-Year Plan” 211 Construction Project of Shanghai University |
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Keywords: | iterative learning optimization control tracking error batch processes |
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