Formal Analysis of the Sampling Behavior of Stochastic Event-Triggered Control

Giannis Delimpaltadakis (Corresponding author), Luca Laurenti, Manuel Mazo

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Analyzing event-triggered control's (ETC) sampling behavior is of paramount importance, as it enables formal assessment of its sampling performance and prediction of its sampling patterns. In this work, we formally analyze the sampling behavior of stochastic linear periodic ETC (PETC) systems by computing bounds on associated metrics. Specifically, we consider functions over sequences of state measurements and intersampling times that can be expressed as average, multiplicative or cumulative rewards, and introduce their expectations as metrics on PETC's sampling behavior. We compute bounds on these expectations, by constructing Interval Markov Chains equipped with suitable reward functions, that abstract stochastic PETC's sampling behavior. Our results are illustrated on a numerical example, for which we compute bounds on the expected average intersampling time and on the probability of triggering with the maximum possible intersampling time in a finite horizon.

Original languageEnglish
Article number10321652
Pages (from-to)4491-4505
Number of pages15
JournalIEEE Transactions on Automatic Control
Volume69
Issue number7
DOIs
Publication statusPublished - Jul 2024

Funding

This work was supported by ERC Starting Grant SENTIENT (755953).

Keywords

  • Bounded-parameter Markov decision processes
  • event-triggered control
  • finite abstractions
  • interval Markov decision processes
  • networked control systems
  • stochastic systems

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