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

• 成果类型: Article
• 署名作者: Delimpaltadakis, Giannis; Laurenti, Luca; Mazo Jr, Manuel
• 署名单位: Eindhoven University of Technology; Delft University of Technology
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2023.3333748
• 发表日期: 2024
• 页码: 4491-4505
• 关键词: Measurement; Markov processes; Processor scheduling; probability distribution; Probabilistic logic; optimization; Bounded-parameter Markov decision processes; event-triggered control; finite abstractions; interval Markov decision processes; networked control systems; Stochastic systems

摘要

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.