Publikation: Parallelized POD-based suboptimal economic model predictive control of a state-constrained Boussinesq approximation
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Motivated by an energy efficient building application, we want to optimize a quadratic cost functional subject to the Boussinesq approximation of the Navier-Stokes equations and to bilateral state and control constraints. Since the computation of such an optimal solution is numerically costly, we design an efficient strategy to compute a sub-optimal (but applicationally acceptable) solution with significantly reduced computational effort. We employ an economic Model Predictive Control (MPC) strategy to obtain a feedback control. The MPC sub-problems are based on a linear-quadratic optimal control problem subjected to mixed control and state constraints and a convection-diffusion equation, reduced with proper orthogonal decomposition. To solve each sub-problem, we apply a primal-dual active set strategy. The method can be fully parallelized, which enables the solution of large problems with real-world parameters.
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ANDREJ, Julian, Lars GRÜNE, Luca MECHELLI, Thomas MEURER, Simon PIRKELMANN, Stefan VOLKWEIN, 2022. Parallelized POD-based suboptimal economic model predictive control of a state-constrained Boussinesq approximation. In: Computers & Mathematics with Applications. Elsevier. 2022, 116, pp. 71-81. ISSN 0898-1221. eISSN 1873-7668. Available under: doi: 10.1016/j.camwa.2021.09.004BibTex
@article{Andrej2022Paral-55477.2,
year={2022},
doi={10.1016/j.camwa.2021.09.004},
title={Parallelized POD-based suboptimal economic model predictive control of a state-constrained Boussinesq approximation},
volume={116},
issn={0898-1221},
journal={Computers & Mathematics with Applications},
pages={71--81},
author={Andrej, Julian and Grüne, Lars and Mechelli, Luca and Meurer, Thomas and Pirkelmann, Simon and Volkwein, Stefan}
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<dcterms:abstract xml:lang="eng">Motivated by an energy efficient building application, we want to optimize a quadratic cost functional subject to the Boussinesq approximation of the Navier-Stokes equations and to bilateral state and control constraints. Since the computation of such an optimal solution is numerically costly, we design an efficient strategy to compute a sub-optimal (but applicationally acceptable) solution with significantly reduced computational effort. We employ an economic Model Predictive Control (MPC) strategy to obtain a feedback control. The MPC sub-problems are based on a linear-quadratic optimal control problem subjected to mixed control and state constraints and a convection-diffusion equation, reduced with proper orthogonal decomposition. To solve each sub-problem, we apply a primal-dual active set strategy. The method can be fully parallelized, which enables the solution of large problems with real-world parameters.</dcterms:abstract>
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