Computing the sampling performance of event-triggered control

Gabriel A. De Gleizer; Manuel Mazo

doi:10.1145/3447928.3456635

Computing the sampling performance of event-triggered control

Team Manuel Mazo Jr

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

10 Citations (Scopus)

53 Downloads (Pure)

Abstract

In the context of networked control systems, event-triggered control (ETC) has emerged as a major topic due to its alleged resource usage reduction capabilities. However, this is mainly supported by numerical simulations, and very little is formally known about the traffic generated by ETC. This work devises a method to estimate, and in some cases to determine exactly, the minimum average inter-sample time (MAIST) generated by periodic event-triggered control (PETC) of linear systems. The method involves abstracting the traffic model using a bisimulation refinement algorithm and finding the cycle of minimum average length in the graph associated to it. This always gives a lower bound to the actual MAIST. Moreover, if this cycle turns out to be related to a periodic solution of the closed-loop PETC system, the performance metric is exact.

Original language	English
Title of host publication	Proceedings of the 24th International Conference on Hybrid Systems (HSCC 2021)
Subtitle of host publication	Computation and Control (part of CPS-IoT Week)
Publisher	Association for Computing Machinery (ACM)
Number of pages	7
ISBN (Electronic)	978-1-4503-8339-4
DOIs	https://doi.org/10.1145/3447928.3456635
Publication status	Published - 2021
Event	24th ACM International Conference on Hybrid Systems Computation and Control, HSCC 2021, held as part of the 14th Cyber Physical Systems and Internet-of-Things Week, CPS-IoT Week 2021 - Virtual, Online, United States Duration: 19 May 2021 → 21 May 2021

Conference

Conference	24th ACM International Conference on Hybrid Systems Computation and Control, HSCC 2021, held as part of the 14th Cyber Physical Systems and Internet-of-Things Week, CPS-IoT Week 2021
Country/Territory	United States
City	Virtual, Online
Period	19/05/21 → 21/05/21

Access to Document

10.1145/3447928.3456635

3447928.3456635Final published version, 628 KBLicence: CC BY

Cite this

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title = "Computing the sampling performance of event-triggered control",

abstract = "In the context of networked control systems, event-triggered control (ETC) has emerged as a major topic due to its alleged resource usage reduction capabilities. However, this is mainly supported by numerical simulations, and very little is formally known about the traffic generated by ETC. This work devises a method to estimate, and in some cases to determine exactly, the minimum average inter-sample time (MAIST) generated by periodic event-triggered control (PETC) of linear systems. The method involves abstracting the traffic model using a bisimulation refinement algorithm and finding the cycle of minimum average length in the graph associated to it. This always gives a lower bound to the actual MAIST. Moreover, if this cycle turns out to be related to a periodic solution of the closed-loop PETC system, the performance metric is exact.",

author = "{De Gleizer}, {Gabriel A.} and Manuel Mazo",

year = "2021",

doi = "10.1145/3447928.3456635",

language = "English",

booktitle = "Proceedings of the 24th International Conference on Hybrid Systems (HSCC 2021)",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

note = "24th ACM International Conference on Hybrid Systems Computation and Control, HSCC 2021, held as part of the 14th Cyber Physical Systems and Internet-of-Things Week, CPS-IoT Week 2021 ; Conference date: 19-05-2021 Through 21-05-2021",

}

De Gleizer, GA & Mazo, M 2021, Computing the sampling performance of event-triggered control. in Proceedings of the 24th International Conference on Hybrid Systems (HSCC 2021): Computation and Control (part of CPS-IoT Week). Association for Computing Machinery (ACM), 24th ACM International Conference on Hybrid Systems Computation and Control, HSCC 2021, held as part of the 14th Cyber Physical Systems and Internet-of-Things Week, CPS-IoT Week 2021, Virtual, Online, United States, 19/05/21. https://doi.org/10.1145/3447928.3456635

Computing the sampling performance of event-triggered control. / De Gleizer, Gabriel A.; Mazo, Manuel.
Proceedings of the 24th International Conference on Hybrid Systems (HSCC 2021): Computation and Control (part of CPS-IoT Week). Association for Computing Machinery (ACM), 2021.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Computing the sampling performance of event-triggered control

AU - De Gleizer, Gabriel A.

AU - Mazo, Manuel

PY - 2021

Y1 - 2021

N2 - In the context of networked control systems, event-triggered control (ETC) has emerged as a major topic due to its alleged resource usage reduction capabilities. However, this is mainly supported by numerical simulations, and very little is formally known about the traffic generated by ETC. This work devises a method to estimate, and in some cases to determine exactly, the minimum average inter-sample time (MAIST) generated by periodic event-triggered control (PETC) of linear systems. The method involves abstracting the traffic model using a bisimulation refinement algorithm and finding the cycle of minimum average length in the graph associated to it. This always gives a lower bound to the actual MAIST. Moreover, if this cycle turns out to be related to a periodic solution of the closed-loop PETC system, the performance metric is exact.

AB - In the context of networked control systems, event-triggered control (ETC) has emerged as a major topic due to its alleged resource usage reduction capabilities. However, this is mainly supported by numerical simulations, and very little is formally known about the traffic generated by ETC. This work devises a method to estimate, and in some cases to determine exactly, the minimum average inter-sample time (MAIST) generated by periodic event-triggered control (PETC) of linear systems. The method involves abstracting the traffic model using a bisimulation refinement algorithm and finding the cycle of minimum average length in the graph associated to it. This always gives a lower bound to the actual MAIST. Moreover, if this cycle turns out to be related to a periodic solution of the closed-loop PETC system, the performance metric is exact.

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M3 - Conference contribution

AN - SCOPUS:85104196020

BT - Proceedings of the 24th International Conference on Hybrid Systems (HSCC 2021)

PB - Association for Computing Machinery (ACM)

T2 - 24th ACM International Conference on Hybrid Systems Computation and Control, HSCC 2021, held as part of the 14th Cyber Physical Systems and Internet-of-Things Week, CPS-IoT Week 2021

Y2 - 19 May 2021 through 21 May 2021

ER -

Computing the sampling performance of event-triggered control

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Timing is everything: Analysis and synthesis of traffic patterns in event-triggered control

ETCetera

Cite this

Computing the sampling performance of event-triggered control

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Research output

Timing is everything: Analysis and synthesis of traffic patterns in event-triggered control

Datasets

ETCetera

Cite this