IDEAS home Printed from https://ideas.repec.org/h/spr/spochp/978-3-030-90924-6_11.html
   My bibliography  Save this book chapter

Fast Model Predictive Control of Modular Systems for Continuous Manufacturing of Pharmaceuticals

In: Optimization of Pharmaceutical Processes

Author

Listed:
  • Anastasia Nikolakopoulou

    (Massachusetts Institute of Technology)

  • Matthias von Andrian

    (Massachusetts Institute of Technology)

  • Richard D. Braatz

    (Massachusetts Institute of Technology)

Abstract

In this chapter, methodologies are described for the plant-wide optimization and control of nonlinear modular systems for continuous-flow pharmaceutical manufacturing. First-principles models for such modular systems are formulated as partial differential-algebraic equations (PDAEs). The spatial discretization of PDAEs, to enable their numerical solution with standard solvers, usually results in a very high number of states. Quadratic dynamic matrix control (QDMC) is an implementable approach for the real-time control of systems with very high state dimension, by using a linear input-output model so that the resulting optimization does not depend on the number of states. To address the strong nonlinearities in these modular systems, linear input-output model construction methodologies are described that can provide good closed-loop performance. Additionally, dynamic optimization of dynamical plant operations such as startup is formulated as a nonlinear program. The dynamic optimization determines optimal trajectories which are used as setpoints for QDMC to control the plant. Results are presented for a computational case study for the upstream synthesis of atropine in a modular continuous-flow system. Dynamic optimization and closed-loop simulation results are presented for plant operations under various disturbance and time-invariant parametric uncertainty scenarios.

Suggested Citation

  • Anastasia Nikolakopoulou & Matthias von Andrian & Richard D. Braatz, 2022. "Fast Model Predictive Control of Modular Systems for Continuous Manufacturing of Pharmaceuticals," Springer Optimization and Its Applications, in: Antonios Fytopoulos & Rohit Ramachandran & Panos M. Pardalos (ed.), Optimization of Pharmaceutical Processes, pages 289-322, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-90924-6_11
    DOI: 10.1007/978-3-030-90924-6_11
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:spochp:978-3-030-90924-6_11. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.