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Numerical Methods for Optimal Boundary Control of Advection-Diffusion-Reaction Systems

Marcus Johan Schytt, John Bagterp Jørgensen

Abstract

This paper considers the optimal boundary control of chemical systems described by advection-diffusion-reaction (ADR) equations. We use a discontinuous Galerkin finite element method (DG-FEM) for the spatial discretization of the governing partial differential equations, and the optimal control problem is directly discretized using multiple shooting. The temporal discretization and the corresponding sensitivity calculations are achieved by an explicit singly diagonally-implicit Runge Kutta (ESDIRK) method. ADR systems arise in process systems engineering and their operation can potentially be improved by nonlinear model predictive control (NMPC). We demonstrate a numerical approach for the solution to their optimal control problems (OCPs) in a chromatography case study. Preparative liquid chromatography is an important downstream process in biopharmaceutical manufacturing. We show that multi-step elution trajectories for batch processes can be optimized for economic objectives, providing superior performance compared to classical gradient elution trajectories.

Numerical Methods for Optimal Boundary Control of Advection-Diffusion-Reaction Systems

Abstract

This paper considers the optimal boundary control of chemical systems described by advection-diffusion-reaction (ADR) equations. We use a discontinuous Galerkin finite element method (DG-FEM) for the spatial discretization of the governing partial differential equations, and the optimal control problem is directly discretized using multiple shooting. The temporal discretization and the corresponding sensitivity calculations are achieved by an explicit singly diagonally-implicit Runge Kutta (ESDIRK) method. ADR systems arise in process systems engineering and their operation can potentially be improved by nonlinear model predictive control (NMPC). We demonstrate a numerical approach for the solution to their optimal control problems (OCPs) in a chromatography case study. Preparative liquid chromatography is an important downstream process in biopharmaceutical manufacturing. We show that multi-step elution trajectories for batch processes can be optimized for economic objectives, providing superior performance compared to classical gradient elution trajectories.
Paper Structure (17 sections, 50 equations, 3 figures, 4 tables)

This paper contains 17 sections, 50 equations, 3 figures, 4 tables.

Figures (3)

  • Figure 1: Outlet profiles for optimal gradient elution with duration $T=40$ min.
  • Figure 2: Outlet profiles for optimal controls for $N_\mathcal{S} = 8$ (solid) and $N_\mathcal{S} = 24$ (dashed) shooting intervals.
  • Figure 3: Outlet profiles for optimal controls with duration $T=32$ min (top) and $T=40$ (bottom).