$\mathcal{H}_2$ Model Reduction for Large-Scale Linear Dynamical Systems

Virginia Tech

Indexed incrossref

Abstract

The optimal $\mathcal{H}_2$ model reduction problem is of great importance in the area of dynamical systems and simulation. In the literature, two independent frameworks have evolved focusing either on solution of Lyapunov equations on the one hand or interpolation of transfer functions on the other, without any apparent connection between the two approaches. In this paper, we develop a new unifying framework for the optimal $\mathcal{H}_2$ approximation problem using best approximation properties in the underlying Hilbert space. This new framework leads to a new set of local optimality conditions taking the form of a structured orthogonality condition. We show that the existing Lyapunov- and…

Citation impact

665
total citations
FWCI
19.42
Percentile
100%
References
38
Citations per year

Authors

3

Topics & keywords

Keywords
  • Mathematics
  • Interpolation (computer graphics)
  • Hilbert space
  • Reduction (mathematics)
  • Applied mathematics
  • Orthogonality
  • Dynamical systems theory
  • Lyapunov function
No related works found for this paper.

Funding