[图书][B] Model order reduction for PDE constrained optimization
The optimization and control of systems governed by partial differential equations (PDEs)
usually requires numerous evaluations of the forward problem or the optimality system …
usually requires numerous evaluations of the forward problem or the optimality system …
Deep model predictive flow control with limited sensor data and online learning
The control of complex systems is of critical importance in many branches of science,
engineering, and industry, many of which are governed by nonlinear partial differential …
engineering, and industry, many of which are governed by nonlinear partial differential …
[图书][B] Model order reduction for differential-algebraic equations: a survey
In this paper, we discuss the model order reduction problem for descriptor systems, that is,
systems with dynamics described by differential-algebraic equations. We focus on linear …
systems with dynamics described by differential-algebraic equations. We focus on linear …
Operator inference and physics-informed learning of low-dimensional models for incompressible flows
Reduced-order modeling has a long tradition in computational fluid dynamics. The ever-
increasing significance of data for the synthesis of low-order models is well reflected in the …
increasing significance of data for the synthesis of low-order models is well reflected in the …
A numerical comparison of different solvers for large-scale, continuous-time algebraic Riccati equations and LQR problems
In this paper, we discuss numerical methods for solving large-scale continuous-time
algebraic Riccati equations. These methods have been the focus of intensive research in …
algebraic Riccati equations. These methods have been the focus of intensive research in …
Matrix Equations, Sparse Solvers: M-MESS-2.0.1—Philosophy, Features, and Application for (Parametric) Model Order Reduction
Matrix equations are omnipresent in (numerical) linear algebra and systems theory.
Especially in model order reduction (MOR), they play a key role in many balancing-based …
Especially in model order reduction (MOR), they play a key role in many balancing-based …
Low-complexity linear parameter-varying approximations of incompressible Navier-Stokes equations for truncated state-dependent Riccati feedback
J Heiland, SWR Werner - IEEE Control Systems Letters, 2023 - ieeexplore.ieee.org
Nonlinear feedback design via state-dependent Riccati equations is well established but
unfeasible for large-scale systems because of computational costs. If the system can be …
unfeasible for large-scale systems because of computational costs. If the system can be …
Moment‐matching based model reduction for Navier–Stokes type quadratic‐bilinear descriptor systems
We discuss a Krylov subspace projection method for model reduction of a special class of
quadratic‐bilinear descriptor systems. The goal is to extend the two‐sided moment …
quadratic‐bilinear descriptor systems. The goal is to extend the two‐sided moment …
Linear-quadratic optimal control of differential-algebraic systems: the infinite time horizon problem with zero terminal state
In this work we revisit the linear-quadratic optimal control problem for differential-algebraic
systems on the infinite time horizon with zero terminal state. Based on the recently …
systems on the infinite time horizon with zero terminal state. Based on the recently …
Example setups of Navier-Stokes equations with control and observation: Spatial discretization and representation via linear-quadratic matrix coefficients
We provide spatial discretizations of nonlinear incompressible Navier-Stokes equations with
inputs and outputs in the form of matrices ready to use in any numerical linear algebra …
inputs and outputs in the form of matrices ready to use in any numerical linear algebra …