# Model Order Reduction for Linear and Nonlinear Systems: A System-Theoretic Perspective

@article{Baur2014ModelOR, title={Model Order Reduction for Linear and Nonlinear Systems: A System-Theoretic Perspective}, author={Ulrike Baur and Peter Benner and Lihong Feng}, journal={Archives of Computational Methods in Engineering}, year={2014}, volume={21}, pages={331-358} }

In the past decades, Model Order Reduction (MOR) has demonstrated its robustness and wide applicability for simulating large-scale mathematical models in engineering and the sciences. [] Key Result Besides reviewing existing methods and the computational techniques needed to implement them, open issues are discussed, and some new results are proposed.

## 259 Citations

### A New Framework for Model Reduction of Complex Nonlinear Dynamical Systems

- Computer Science
- 2017

This dissertation develops a framework which measures the robustness and persistency of reduced order models, and uses SOD to identify the dynamically relevant modal structures of the control system and extends the proposed approach to model order reduction of nonlinear control systems.

### Model Order Reduction for Differential-Algebraic Equations: A Survey

- Computer Science, Mathematics
- 2017

This paper discusses the model order reduction problem for descriptor systems, that is, systems with dynamics described by differential-algebraic equations, and reviews efforts in extending popular methods related to balanced truncation and rational interpolation to descriptor systems.

### A Structure-preserving Model Reduction Algorithm for Dynamical Systems with Nonlinear Frequency Dependence

- Computer Science
- 2016

### A Critical Exposition of Model Order Reduction Techniques: Application to a Slewing Flexible Beam

- Computer ScienceArchives of Computational Methods in Engineering
- 2019

This review paper deals with MOR by critically comparing the most popular MOR techniques from the fields of structural dynamics, numerical mathematics and systems and control, and a table summarizing their most important features is proposed.

### On the use of modal derivatives for nonlinear model order reduction

- Engineering, Mathematics
- 2016

Modal derivative is an approach to compute a reduced basis for model order reduction of large‐scale nonlinear systems that typically stem from the discretization of partial differential equations. In…

### Computation-Efficient Simulation of Nonlinear Thermal Boundary Conditions for Large-Scale Models

- Computer ScienceIEEE Control Systems Letters
- 2018

A simplified nonlinear system description is proposed by decoupling non linear affected states, performing MOR of the remaining linear term and apply calculated projection to the nonlinear affected part, which prospectively enables high-performance approximation of non linear system behavior.

### Mathematical and Computer Modelling of Dynamical Systems Methods , Tools and Applications in Engineering and Related Sciences

- Computer Science
- 2016

Numerical examples demonstrate that the modified ERA algorithm with tangentially interpolated data produces accurate reduced models while, at the same time, reducing the computational cost and memory requirements significantly compared to the standard ERA.

### An Error Bound for Low Order Approximation of Dynamical Systems Subjected to Initial Conditions

- EngineeringTEMA (São Carlos)
- 2018

In recent years, a great effort has been taken focused on the development of reduced order modeling techniques of dynamical systems. This necessity is pushed by the requirement for efficient…

### A new approach to model reduction of nonlinear control systems using smooth orthogonal decomposition

- EngineeringInternational Journal of Robust and Nonlinear Control
- 2018

A new approach to model order reduction of nonlinear control systems is aimed at developing persistent reduced order models (ROMs) that are robust to the changes in system's energy level. A…

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