Average Communication Rate for Event-Triggered Stochastic Control Systems

Fuente: arXiv
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Main Authors: Zhang, Zengjie, Liu, Qingchen, Mamduhi, Mohammad H., Hirche, Sandra
Format: Preprint
Published: 2023
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author Zhang, Zengjie
Liu, Qingchen
Mamduhi, Mohammad H.
Hirche, Sandra
author_facet Zhang, Zengjie
Liu, Qingchen
Mamduhi, Mohammad H.
Hirche, Sandra
contents Quantifying the average communication rate (ACR) of a networked event-triggered stochastic control system (NET-SCS) with deterministic thresholds is challenging due to the non-stationary nature of the system's stochastic processes. For a NET-SCS, the nonlinear statistics propagation of the network communication status brought up by deterministic thresholds makes the precise computation of ACR difficult. Previous work used to over-simplify the computation using a Gaussian distribution without incorporating this nonlinearity, leading to sacrificed precision. This paper proposes both analytical and numerical approaches to predict the exact ACR for a NET-SCS using a recursive model. We use theoretical analysis and a numerical study to qualitatively evaluate the deviation gap of the conventional approach that ignores the side information. The accuracy of our proposed method, alongside its comparison with the simplified results of the conventional approach, is validated by experimental studies. Our work is promising to benefit the efficient resource planning of networked control systems with limited communication resources by providing accurate ACR computation.
format Preprint
id arxiv_https___arxiv_org_abs_2301_05445
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Average Communication Rate for Event-Triggered Stochastic Control Systems
Zhang, Zengjie
Liu, Qingchen
Mamduhi, Mohammad H.
Hirche, Sandra
Signal Processing
Quantifying the average communication rate (ACR) of a networked event-triggered stochastic control system (NET-SCS) with deterministic thresholds is challenging due to the non-stationary nature of the system's stochastic processes. For a NET-SCS, the nonlinear statistics propagation of the network communication status brought up by deterministic thresholds makes the precise computation of ACR difficult. Previous work used to over-simplify the computation using a Gaussian distribution without incorporating this nonlinearity, leading to sacrificed precision. This paper proposes both analytical and numerical approaches to predict the exact ACR for a NET-SCS using a recursive model. We use theoretical analysis and a numerical study to qualitatively evaluate the deviation gap of the conventional approach that ignores the side information. The accuracy of our proposed method, alongside its comparison with the simplified results of the conventional approach, is validated by experimental studies. Our work is promising to benefit the efficient resource planning of networked control systems with limited communication resources by providing accurate ACR computation.
title Average Communication Rate for Event-Triggered Stochastic Control Systems
topic Signal Processing
url https://arxiv.org/abs/2301.05445