Handling model uncertainty in control of a pressure swing adsorption unit for syngas purification: A multi-model zone control scheme-based robust model predictive control strategy

• Type: Article in International Scientific Journal
• Date: 2023

Authors

Martins, MAF (Author) Other; Rodrigues, AE (Author) Other; Loureiro, JM (Author) Other; Ana M. Ribeiro (Author) FEUP; Nogueira, IBR (Author) Other

Journal

Title: Separation and Purification Technology

Vol. 306

ISSN: 1383-5866

Publisher: Elsevier

Indexing

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Other information

Authenticus ID: P-00X-G2X

DOI: 10.1016/j.seppur.2022.122668

Abstract (EN): The application of a robustly stabilizing model predictive control (MPC) strategy to a pressure swing adsorption (PSA) unit, hitherto unexplored in the literature, is addressed in this work. Here, a set of linear models to handle model uncertainties describes the PSA nonlinear dynamic behaviour. Each model represents a different operating condition of the PSA, generating a multi-model uncertainty description. In addition to incorporating the multi-model uncertainty, the proposed MPC control law deals with a controlled output zone tracking scheme to systematically accommodate typical cyclic steady states of a PSA process. From the industrial standpoint, economic targets on process variables (controlled outputs, manipulated inputs, or both) are also incorporated into the robust control method. A Real-Time Optimizer usually defines these targets, making up a two-layer control scheme. The effectiveness of the robust MPC is evaluated in a syngas purification process via a single bed, six-step PSA unit composed of a porous amino-functionalized titanium terephthalate MIL-125-type MOF adsorbent.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12