Abstracting the Sampling Behaviour of Stochastic Linear Periodic Event-Triggered Control Systems

Giannis Delimpaltadakis, Luca Laurenti, Manuel Mazo

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

9 Citations (Scopus)

Abstract

Recently, there have been efforts towards understanding the sampling behaviour of event-triggered control (ETC), for obtaining metrics on its sampling performance and predicting its sampling patterns. Finite-state abstractions, capturing the sampling behaviour of ETC systems, have proven promising in this respect. So far, such abstractions have been constructed for non-stochastic systems. Here, inspired by this framework, we abstract the sampling behaviour of stochastic narrow-sense linear periodic ETC (PETC) systems via Interval Markov Chains (IMCs). Particularly, we define functions over sequences of state-measurements and interevent times that can be expressed as discounted cumulative sums of rewards, and compute bounds on their expected values by constructing appropriate IMCs and equipping them with suitable rewards. Finally, we argue that our results are extendable to more general forms of functions, thus providing a generic framework to define and study various ETC sampling indicators.
Original languageEnglish
Title of host publication2021 60th IEEE Conference on Decision and Control (CDC)
PublisherInstitute of Electrical and Electronics Engineers
Pages1287-1294
Number of pages8
ISBN (Electronic)9781665436595
ISBN (Print)978-1-6654-3660-1
DOIs
Publication statusPublished - 1 Feb 2022
Externally publishedYes
Event60th IEEE Conference on Decision and Control, CDC 2021 - Austin, TX, USA, Austin, United States
Duration: 13 Dec 202117 Dec 2021
Conference number: 60
https://2021.ieeecdc.org/

Conference

Conference60th IEEE Conference on Decision and Control, CDC 2021
Abbreviated titleCDC 2021
Country/TerritoryUnited States
CityAustin
Period13/12/2117/12/21
Internet address

Keywords

  • Measurement
  • Conferences
  • Markov processes
  • Control systems

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