Sensitivity Function Trade-Offs for Networks with a String Topology

Richard Pates; Kaoru Yamamoto

doi:10.1109/CDC.2018.8619555

Sensitivity Function Trade-Offs for Networks with a String Topology

Richard Pates, Kaoru Yamamoto

Department of Automatic Control

Kyushu University

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

Abstract

We present two sensitivity function trade-offs that apply to a class of networks with a string topology. In particular we show that a lower bound on the H-infinity norm and a Bode sensitivity relation hold for an entire family of sensitivity functions associated with growing the network. The trade-offs we identify are a direct consequence of growing the network, and can be used to explain why poorly regulated low frequency behaviours emerge in long vehicle platoons even when using dynamic feedback.

Original language	English
Title of host publication	2018 IEEE Conference on Decision and Control, CDC 2018
Publisher	IEEE - Institute of Electrical and Electronics Engineers Inc.
Pages	5869-5873
Number of pages	5
ISBN (Electronic)	9781538613955
DOIs	https://doi.org/10.1109/CDC.2018.8619555
Publication status	Published - 2019 Jan 21
Event	57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States Duration: 2018 Dec 17 → 2018 Dec 19

Conference

Conference	57th IEEE Conference on Decision and Control, CDC 2018
Country/Territory	United States
City	Miami
Period	2018/12/17 → 2018/12/19

Subject classification (UKÄ)

Control Engineering

Access to Document

10.1109/CDC.2018.8619555

Cite this

@inproceedings{253956bc9bcb4e00872956bc8884c896,

title = "Sensitivity Function Trade-Offs for Networks with a String Topology",

abstract = "We present two sensitivity function trade-offs that apply to a class of networks with a string topology. In particular we show that a lower bound on the H-infinity norm and a Bode sensitivity relation hold for an entire family of sensitivity functions associated with growing the network. The trade-offs we identify are a direct consequence of growing the network, and can be used to explain why poorly regulated low frequency behaviours emerge in long vehicle platoons even when using dynamic feedback.",

author = "Richard Pates and Kaoru Yamamoto",

year = "2019",

month = jan,

day = "21",

doi = "10.1109/CDC.2018.8619555",

language = "English",

pages = "5869--5873",

booktitle = "2018 IEEE Conference on Decision and Control, CDC 2018",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "57th IEEE Conference on Decision and Control, CDC 2018 ; Conference date: 17-12-2018 Through 19-12-2018",

}

Pates, R & Yamamoto, K 2019, Sensitivity Function Trade-Offs for Networks with a String Topology. in 2018 IEEE Conference on Decision and Control, CDC 2018., 8619555, IEEE - Institute of Electrical and Electronics Engineers Inc., pp. 5869-5873, 57th IEEE Conference on Decision and Control, CDC 2018, Miami, United States, 2018/12/17. https://doi.org/10.1109/CDC.2018.8619555

TY - GEN

T1 - Sensitivity Function Trade-Offs for Networks with a String Topology

AU - Pates, Richard

AU - Yamamoto, Kaoru

PY - 2019/1/21

Y1 - 2019/1/21

N2 - We present two sensitivity function trade-offs that apply to a class of networks with a string topology. In particular we show that a lower bound on the H-infinity norm and a Bode sensitivity relation hold for an entire family of sensitivity functions associated with growing the network. The trade-offs we identify are a direct consequence of growing the network, and can be used to explain why poorly regulated low frequency behaviours emerge in long vehicle platoons even when using dynamic feedback.

AB - We present two sensitivity function trade-offs that apply to a class of networks with a string topology. In particular we show that a lower bound on the H-infinity norm and a Bode sensitivity relation hold for an entire family of sensitivity functions associated with growing the network. The trade-offs we identify are a direct consequence of growing the network, and can be used to explain why poorly regulated low frequency behaviours emerge in long vehicle platoons even when using dynamic feedback.

U2 - 10.1109/CDC.2018.8619555

DO - 10.1109/CDC.2018.8619555

M3 - Paper in conference proceeding

AN - SCOPUS:85062173036

SP - 5869

EP - 5873

BT - 2018 IEEE Conference on Decision and Control, CDC 2018

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - 57th IEEE Conference on Decision and Control, CDC 2018

Y2 - 17 December 2018 through 19 December 2018

ER -

Sensitivity Function Trade-Offs for Networks with a String Topology

Abstract

Conference

Subject classification (UKÄ)

Access to Document

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Cite this