Iterative Learning Control Applied to Batch Processes: an Overview
نویسندگان
چکیده
With the recent emphasis on batch processing by the emerging industries like the microelectronics and biotechnology, the interest in batch process control has been renewed. In this paper, we present an overview of the Iterative Learning Control (ILC) technique, which can be used to improve tracking control performance in batch processes. We present the fundamental concepts and review the various ILC algorithms, with a particular focus on a model-based algorithm called Q-ILC and an application involving a Rapid Thermal Processing (RTP) system. The study indicates that one can solve a seemingly very difficult multivariable nonlinear tracking problem with relative ease by combining the ILC technique with basic process insights and standard system identification techniques. We also bring forth some related techniques in the literature with the hope of unifying them and also suggest some remaining challenges.
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