English

A Unified Software Framework for Empirical Gramians

Optimization and Control 2016-08-22 v5 Mathematical Software Systems and Control Dynamical Systems

Abstract

A common approach in model reduction is balanced truncation, which is based on gramian matrices classifiying certain attributes of states or parameters of a given dynamic system. Initially restricted to linear systems, the empirical gramians not only extended this concept to nonlinear systems, but also provide a uniform computational method. This work introduces a unified software framework supplying routines for six types of empirical gramians. The gramian types will be discussed and applied in a model reduction framework for multiple-input-multiple-output (MIMO) systems.

Keywords

Cite

@article{arxiv.1301.6879,
  title  = {A Unified Software Framework for Empirical Gramians},
  author = {Christian Himpe and Mario Ohlberger},
  journal= {arXiv preprint arXiv:1301.6879},
  year   = {2016}
}

Comments

Preprint

R2 v1 2026-06-21T23:17:03.391Z