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Optimization Based Adaptive Control of Simulated Moving Beds


S. Abel, M. Mazzotti, G. Erdem, M. Morari, M. Morbidelli

Pacific Basin Conference on Adsorption Science and Technology, Kyongju, Korea, pp. 177-181

In the recent years Simulated Moving Bed (SMB) technology has become more and more attractive for complex separation tasks. To ensure the compliance with product specifications, a robust control is required. In this work a new optimization based adaptive control strategy for the SMB is proposed: A linearized reduced order model, which accounts for the periodic nature of the SMB process is used for online optimization and control purposes. Concentration measurements at the raffinate and extract outlets are used as the feedback information together with a periodic Kalman filter to remove model errors and to handle disturbances. The state estimate from the periodic Kalman filter is then used for the prediction of the outlet concentrations over a pre-defined time horizon. Predicted outlet concentrations constitute the basis for the calculation of the optimal input adjustments, which maximize the productivity and minimize the desorbent consumption subject to constraints on product purities.


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M. Morari

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% Autogenerated BibTeX entry
@InProceedings { AbeEtal:2003:IFA_382,
    author={S. Abel and M. Mazzotti and G. Erdem and M. Morari and M. Morbidelli},
    title={{Optimization Based Adaptive Control of Simulated Moving
    booktitle={Pacific Basin Conference on Adsorption Science and
    address={Kyongju, Korea},
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