Language-based abstractions for dynamical systems

Andrea Vandin*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Ordinary differential equations (ODEs) are the primary means to modelling dynamical systems in many natural and engineering sciences. The number of equations required to describe a system with high heterogeneity limits our capability of effectively performing analyses. This has motivated a large body of research, across many disciplines, into abstraction techniques that provide smaller ODE systems while preserving the original dynamics in some appropriate sense. In this paper we give an overview of a recently proposed computer-science perspective to this problem, where ODE reduction is recast to finding an appropriate equivalence relation over ODE variables, akin to classical models of computation based on labelled transition systems.

Original languageEnglish
JournalElectronic Proceedings in Theoretical Computer Science, EPTCS
Volume250
Pages (from-to)15-24
Number of pages10
ISSN2075-2180
DOIs
Publication statusPublished - 12 Jul 2017
Externally publishedYes

Cite this

@article{818676e0237b472b9cfd02f85ecd7475,
title = "Language-based abstractions for dynamical systems",
abstract = "Ordinary differential equations (ODEs) are the primary means to modelling dynamical systems in many natural and engineering sciences. The number of equations required to describe a system with high heterogeneity limits our capability of effectively performing analyses. This has motivated a large body of research, across many disciplines, into abstraction techniques that provide smaller ODE systems while preserving the original dynamics in some appropriate sense. In this paper we give an overview of a recently proposed computer-science perspective to this problem, where ODE reduction is recast to finding an appropriate equivalence relation over ODE variables, akin to classical models of computation based on labelled transition systems.",
author = "Andrea Vandin",
year = "2017",
month = "7",
day = "12",
doi = "10.4204/EPTCS.250.2",
language = "English",
volume = "250",
pages = "15--24",
journal = "Electronic Proceedings in Theoretical Computer Science",
issn = "2075-2180",
publisher = "Open Publishing Association",

}

Language-based abstractions for dynamical systems. / Vandin, Andrea.

In: Electronic Proceedings in Theoretical Computer Science, EPTCS, Vol. 250, 12.07.2017, p. 15-24.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Language-based abstractions for dynamical systems

AU - Vandin, Andrea

PY - 2017/7/12

Y1 - 2017/7/12

N2 - Ordinary differential equations (ODEs) are the primary means to modelling dynamical systems in many natural and engineering sciences. The number of equations required to describe a system with high heterogeneity limits our capability of effectively performing analyses. This has motivated a large body of research, across many disciplines, into abstraction techniques that provide smaller ODE systems while preserving the original dynamics in some appropriate sense. In this paper we give an overview of a recently proposed computer-science perspective to this problem, where ODE reduction is recast to finding an appropriate equivalence relation over ODE variables, akin to classical models of computation based on labelled transition systems.

AB - Ordinary differential equations (ODEs) are the primary means to modelling dynamical systems in many natural and engineering sciences. The number of equations required to describe a system with high heterogeneity limits our capability of effectively performing analyses. This has motivated a large body of research, across many disciplines, into abstraction techniques that provide smaller ODE systems while preserving the original dynamics in some appropriate sense. In this paper we give an overview of a recently proposed computer-science perspective to this problem, where ODE reduction is recast to finding an appropriate equivalence relation over ODE variables, akin to classical models of computation based on labelled transition systems.

U2 - 10.4204/EPTCS.250.2

DO - 10.4204/EPTCS.250.2

M3 - Journal article

AN - SCOPUS:85030158000

VL - 250

SP - 15

EP - 24

JO - Electronic Proceedings in Theoretical Computer Science

JF - Electronic Proceedings in Theoretical Computer Science

SN - 2075-2180

ER -