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

Anastasia Nikolakopoulou (), Matthias von Andrian () and Richard D. Braatz ()
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Anastasia Nikolakopoulou: Massachusetts Institute of Technology
Matthias von Andrian: Massachusetts Institute of Technology
Richard D. Braatz: Massachusetts Institute of Technology

A chapter in Optimization of Pharmaceutical Processes, 2022, pp 289-322 from Springer

Abstract: 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.

Keywords: Pharmaceutical manufacturing; Continuous manufacturing; Plant-wide control; Model predictive control; Dynamic optimization; Model-based control (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-90924-6_11

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DOI: 10.1007/978-3-030-90924-6_11

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