Abstract
Sheet and film processes are inherently difficult to identify. The extensive interactions across the machine result in the process transfer function having a large condition number, and it is well-known that identifying the gain directionality for such processes is challenging (as discussed in Section 2.5). The input signals used for process identification are constrained, which limit the signal-to-noise ratios obtained during experimental input-output testing. Sheet and film processes have a high input-output dimensionality, implying that a significant number of model parameters must be identified. At the same time, the quantity of experimental data that can be collected is usually low, in that traversing sensors are typically used, which measure a limited portion of the profile at any given time. Also, the time period during which input-output experiments can be carried out is also limited. For example, a film extruder may change polymer grades after only eight hours, in which case the entire time period for conducting experiments must be substantially less than eight hours for the identified model to be available long enough to be used for closed-loop control purposes for the current polymer grade. Typically, the input-output experimental runs are constrained by various staff (e.g., process operators, plant managers) to run no longer than 20 minutes.
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© 2000 Springer-Verlag London
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Featherstone, A.P., VanAntwerp, J.G., Braatz, R.D. (2000). Model Requirements and Process Identification. In: Identification and Control of Sheet and Film Processes. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-0413-1_4
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DOI: https://doi.org/10.1007/978-1-4471-0413-1_4
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1134-4
Online ISBN: 978-1-4471-0413-1
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