Nonlinear model predictive control of integrated process systems

Michael Baldea, Prodromos Daoutidis, Zoltan K. Nagy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

The paper considers the NMPC of process systems that feature a dynamic behavior with multiple time scales, as a consequence of process integration. The process dynamics are modeled via a singularly perturbed system of differential equations in nonstandard form. A framework for simultaneous model reduction and composite controller synthesis is introduced, relying on linear feedback control for the fast dynamics and NMPC for the slow dynamics (using the corresponding reduced order, non-stiff model). Precise dimensions for the state-space realization of the fast and slow components of the system dynamics are provided and the stability and optimality properties of the proposed control framework are characterized. Furthermore, it is argued that this framework reduces online computation times and a simulation case study is presented for illustration.

Original languageEnglish (US)
Title of host publication8th IFAC Symposium on Nonlinear Control Systems, NOLCOS 2010
PublisherIFAC Secretariat
Pages1040-1045
Number of pages6
Edition14
ISBN (Print)9783902661807
DOIs
StatePublished - 2010

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number14
Volume43
ISSN (Print)1474-6670

Bibliographical note

Funding Information:
Partial support by the National Science Foundation, grant CBET− 0756363, is gratefully acknowledged.

Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

Keywords

  • Model reduction
  • Nonlinear model predictive control
  • Plant-wide control
  • Process integration

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