On polytopic approximations of systems with time-varying input delays

R.H. Gielen, S. Olaru, M. Lazar

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

10 Citations (Scopus)

Abstract

Networked control systems (NCS) have recently received an increasing attention from the control systems community. One of the major problems in NCS is how to model the highly nonlinear terms caused by uncertain delays such as time-varying input delays. A straightforward solution is to employ polytopic approximations. In this paper we develop a novel method for creating discrete-time models for systems with time-varying input delays based on polytopic approximations. The proposed method is compared to several other existing approaches in terms of quality, complexity and scalability. Furthermore, its suitability for model predictive control is demonstrated.
LanguageEnglish
Title of host publicationNonlinear model predictive control : towards new challenging applications
EditorsL. Magni, D.M. Raimondo, F. Allgoewer
Place of PublicationBerlin
PublisherSpringer
Pages225-233
Number of pages8
ISBN (Print)978-3-642-01094-1
DOIs
StatePublished - 2009

Publication series

NameLecture Notes in Control and Information Sciences
Volume384
ISSN (Print)0170-8643

Fingerprint

Networked control systems
Model predictive control
Scalability
Control systems

Cite this

Gielen, R. H., Olaru, S., & Lazar, M. (2009). On polytopic approximations of systems with time-varying input delays. In L. Magni, D. M. Raimondo, & F. Allgoewer (Eds.), Nonlinear model predictive control : towards new challenging applications (pp. 225-233). (Lecture Notes in Control and Information Sciences; Vol. 384). Berlin: Springer. DOI: 10.1007/978-3-642-01094-1_18
Gielen, R.H. ; Olaru, S. ; Lazar, M./ On polytopic approximations of systems with time-varying input delays. Nonlinear model predictive control : towards new challenging applications. editor / L. Magni ; D.M. Raimondo ; F. Allgoewer. Berlin : Springer, 2009. pp. 225-233 (Lecture Notes in Control and Information Sciences).
@inbook{b80366b81ec247f78097a7dad7918d11,
title = "On polytopic approximations of systems with time-varying input delays",
abstract = "Networked control systems (NCS) have recently received an increasing attention from the control systems community. One of the major problems in NCS is how to model the highly nonlinear terms caused by uncertain delays such as time-varying input delays. A straightforward solution is to employ polytopic approximations. In this paper we develop a novel method for creating discrete-time models for systems with time-varying input delays based on polytopic approximations. The proposed method is compared to several other existing approaches in terms of quality, complexity and scalability. Furthermore, its suitability for model predictive control is demonstrated.",
author = "R.H. Gielen and S. Olaru and M. Lazar",
year = "2009",
doi = "10.1007/978-3-642-01094-1_18",
language = "English",
isbn = "978-3-642-01094-1",
series = "Lecture Notes in Control and Information Sciences",
publisher = "Springer",
pages = "225--233",
editor = "L. Magni and D.M. Raimondo and F. Allgoewer",
booktitle = "Nonlinear model predictive control : towards new challenging applications",
address = "Germany",

}

Gielen, RH, Olaru, S & Lazar, M 2009, On polytopic approximations of systems with time-varying input delays. in L Magni, DM Raimondo & F Allgoewer (eds), Nonlinear model predictive control : towards new challenging applications. Lecture Notes in Control and Information Sciences, vol. 384, Springer, Berlin, pp. 225-233. DOI: 10.1007/978-3-642-01094-1_18

On polytopic approximations of systems with time-varying input delays. / Gielen, R.H.; Olaru, S.; Lazar, M.

Nonlinear model predictive control : towards new challenging applications. ed. / L. Magni; D.M. Raimondo; F. Allgoewer. Berlin : Springer, 2009. p. 225-233 (Lecture Notes in Control and Information Sciences; Vol. 384).

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

TY - CHAP

T1 - On polytopic approximations of systems with time-varying input delays

AU - Gielen,R.H.

AU - Olaru,S.

AU - Lazar,M.

PY - 2009

Y1 - 2009

N2 - Networked control systems (NCS) have recently received an increasing attention from the control systems community. One of the major problems in NCS is how to model the highly nonlinear terms caused by uncertain delays such as time-varying input delays. A straightforward solution is to employ polytopic approximations. In this paper we develop a novel method for creating discrete-time models for systems with time-varying input delays based on polytopic approximations. The proposed method is compared to several other existing approaches in terms of quality, complexity and scalability. Furthermore, its suitability for model predictive control is demonstrated.

AB - Networked control systems (NCS) have recently received an increasing attention from the control systems community. One of the major problems in NCS is how to model the highly nonlinear terms caused by uncertain delays such as time-varying input delays. A straightforward solution is to employ polytopic approximations. In this paper we develop a novel method for creating discrete-time models for systems with time-varying input delays based on polytopic approximations. The proposed method is compared to several other existing approaches in terms of quality, complexity and scalability. Furthermore, its suitability for model predictive control is demonstrated.

U2 - 10.1007/978-3-642-01094-1_18

DO - 10.1007/978-3-642-01094-1_18

M3 - Chapter

SN - 978-3-642-01094-1

T3 - Lecture Notes in Control and Information Sciences

SP - 225

EP - 233

BT - Nonlinear model predictive control : towards new challenging applications

PB - Springer

CY - Berlin

ER -

Gielen RH, Olaru S, Lazar M. On polytopic approximations of systems with time-varying input delays. In Magni L, Raimondo DM, Allgoewer F, editors, Nonlinear model predictive control : towards new challenging applications. Berlin: Springer. 2009. p. 225-233. (Lecture Notes in Control and Information Sciences). Available from, DOI: 10.1007/978-3-642-01094-1_18