Model comparison and simplification

Lennart Andersson, Anders Rantzer, Carolyn Beck

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper we consider comparison and simplification of dynamical models. These models may contain non-linearities as well as uncertainty, where both are described using Integral Quadratic Constraints (IQCs). The proposed method includes simplification by truncation and singular perturbation approximation as special cases. The simplification error is defined in terms of the L2-induced gain. It is shown that each non-linear or uncertain system component can be assigned a positive value, computable by convex optimization, such that the simplification error is always bounded by the sum of these values corresponding to the simplified components.

Original languageEnglish (US)
Pages (from-to)157-181
Number of pages25
JournalInternational Journal of Robust and Nonlinear Control
Volume9
Issue number3
DOIs
StatePublished - Mar 1 1999
Externally publishedYes

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Chemical Engineering(all)
  • Biomedical Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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