Analysis of Predictor Feedback for Time-Varying Delays that may Assume Zero Value

Yonglong Liao, Shu Xia Tang, Fucheng Liao, Miroslav Krstic

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

For linear systems with a time-varying input delay, the predictor feedback controller and exponential stability have been established. However, the now-classical approach of representing the delay by a transport partial differential equation (PDE) on a strictly positive and constant spatial domain precludes the possibility of the delay assuming the zero value at any time instant. To eliminate this limitation, we provide a new representation of the delay by a transport equation with a time-varying spatial domain. The resulting backstepping approach leads to the same predictor feedback that was previously designed by the last author. However, the controller derivation and the stability analysis are quite different, even though both the controller and the assumptions are the same. A representative example is provided to illustrate the methodology and results.

Original languageEnglish
Title of host publication2020 59th IEEE Conference on Decision and Control, CDC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1957-1962
Number of pages6
ISBN (Electronic)9781728174471
DOIs
StatePublished - Dec 14 2020
Event59th IEEE Conference on Decision and Control, CDC 2020 - Virtual, Jeju Island, Korea, Republic of
Duration: Dec 14 2020Dec 18 2020

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2020-December
ISSN (Print)0743-1546

Conference

Conference59th IEEE Conference on Decision and Control, CDC 2020
Country/TerritoryKorea, Republic of
CityVirtual, Jeju Island
Period12/14/2012/18/20

Keywords

  • Time-varying delay
  • backstepping
  • coupled transport PDE-ODE
  • predictor
  • time-varying spatial domain

Fingerprint

Dive into the research topics of 'Analysis of Predictor Feedback for Time-Varying Delays that may Assume Zero Value'. Together they form a unique fingerprint.

Cite this