EconPapers    
Economics at your fingertips  
 

$$\mathcal {H}_2$$ H 2 -gap Model Reduction for Stabilizable and Detectable Systems

Tobias Breiten (), Christopher Beattie () and Serkan Gugercin ()
Additional contact information
Tobias Breiten: Technical University of Berlin, Institute of Mathematics
Christopher Beattie: Virginia Tech, Department of Mathematics
Serkan Gugercin: Virginia Tech, Department of Mathematics

A chapter in Realization and Model Reduction of Dynamical Systems, 2022, pp 317-334 from Springer

Abstract: Abstract We formulate here an approach to model reduction that is well-suited for linear time-invariant control systems that are stabilizable and detectable but may otherwise be unstable. We introduce a modified $$\mathcal {H}_2$$ H 2 -error metric, the $$\mathcal {H}_2$$ H 2 -gap, that provides an effective measure of model fidelity in this setting. While the direct evaluation of the $$\mathcal {H}_2$$ H 2 -gap requires the solutions of a pair of algebraic Riccati equations associated with related closed-loop systems, we are able to work entirely within an interpolatory framework, developing algorithms and supporting analysis that do not reference full-order closed-loop Gramians. This leads to a computationally effective strategy yielding reduced models designed so that the corresponding reduced closed-loop systems will interpolate the full-order closed-loop system at specially adapted interpolation points, without requiring evaluation of the full-order closed-loop system nor even computation of the feedback law that determines it. The analytical framework and computational algorithm presented here provides an effective new approach toward constructing reduced-order models for unstable systems. Numerical examples for an unstable convection diffusion equation and a linearized incompressible Navier-Stokes equation illustrate the effectiveness of this approach.

Keywords: $$\mathcal {H}_2$$ H 2 optimality; Unstable systems; Interpolation; Riccati equations (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-95157-3_17

Ordering information: This item can be ordered from
http://www.springer.com/9783030951573

DOI: 10.1007/978-3-030-95157-3_17

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-05-22
Handle: RePEc:spr:sprchp:978-3-030-95157-3_17