Model Reduction and Control of a Compressible Channel Flow with Combustion

Pyta, Lorenz; Hakenberg, Mathias; Abel, Dirk

doi:10.3182/20140824-6-za-1003.01927

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…While the mechanical subsystem has been removed in (14), it is still taking into account the full temporal evolution of the temperature profile T(z, t). This temporal evolution is characterized by faster periodic fluctuations of T(z, t) due to the mechanical motion of the radiator and a slower evolution of the average temperature profile.…”

Section: Averaging Over Each Cyclementioning

confidence: 99%

“…Reduced-order models (ROMs) for PDEs based on the POD-Galerkin technique were already successfully employed in model predictive controllers in the past. 14 A very efficient reduced-order model of the investigated process, which avoids several existing pitfalls like an intermediate reconstruction of temperature distributions, 15 was presented by the authors in previous works. 16 The contribution of this article is to derive a nonlinear model predictive control (NMPC) concept for a heating process with a movable radiator, which causes the system to be a nonlinear IPDE.…”

Section: Introductionmentioning

confidence: 99%

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Nonlinear model predictive control of a radiative heating process with movable radiators

Rötzer

Dörschel

Deutschmann‐Olek

et al. 2022

Intl J Robust & Nonlinear

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A nonlinear model predictive control concept for a heating process with dominant radiation and movable radiators is derived. Such processes can be described by a nonlinear integro‐partial differential equation with full domain coupling for the thermal subsystem and an ordinary differential equation for the mechanical subsystem. For model‐based control, a reduced‐order model based on a tailored proper orthogonal decomposition Galerkin approach is used. To enable real‐time capability, a rigorous formulation of the optimization problem is presented, which allows to split the optimization problem into two subproblems using a separation of time scales. These subproblems are subsequently simplified by employing averaging methods and appropriate analytical solutions. An extensive simulation study illustrates the high performance and fast calculation times of the proposed control concept.

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Section: Averaging Over Each Cyclementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nonlinear model predictive control of a radiative heating process with movable radiators

Rötzer

Dörschel

Deutschmann‐Olek

et al. 2022

Intl J Robust & Nonlinear

Self Cite

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show abstract

“…Such controllers will solve the finite horizon open-loop control problem with use of the reduced order model of the plant (derived by POD-Galerkin) and repeat this process in every time step (see e.g. [10]). …”

Section: Introductionmentioning

confidence: 99%

Optimal feedback control of the incompressible Navier-Stokes-Equations using reduced order models

Pyta

Herty

Abel

2015

2015 54th IEEE Conference on Decision and Control (CDC)

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A novel scheme for an optimal feedback-control of distributed parameter systems is proposed. Therefore, the optimal control problem for the two-dimensional incompressible Navier-Stokes-Equations with an actuation via boundaryconditions is set up. Afterwards the Navier-Stokes-Equations and their adjoint equations are solved numerically. A model reduction is performed for both solutions using the PODGalerkin procedure. The optimal feedback control is computed online from the reduced order models in each time step without need of further optimization. Results are shown for closed-loop simulations with the Navier-Stokes-Equations.

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Online Model Adaption of Reduced Order Models for Fluid Flows

Pyta

Abel

2017

IFAC-PapersOnLine

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Model Reduction and Control of a Compressible Channel Flow with Combustion

Cited by 7 publications

References 11 publications

Nonlinear model predictive control of a radiative heating process with movable radiators

Nonlinear model predictive control of a radiative heating process with movable radiators

Optimal feedback control of the incompressible Navier-Stokes-Equations using reduced order models

Online Model Adaption of Reduced Order Models for Fluid Flows

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