Sparse sensor selection for distributed systems: an l1-relaxation approach

We study the problem of sensor selection for distributed systems, where a large number of sensors are located spatially in many different locations. Specifically, we consider both perfect and packet-dropping communication channels. While the original problem is NP-hard, by adopting a sparse design,...

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Main Authors: Zhong, Yuxing, Yang, Nachuan, Huang, Lingying, Shi, Guodong, Shi, Ling
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/179227
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1792272024-07-23T04:46:29Z Sparse sensor selection for distributed systems: an l1-relaxation approach Zhong, Yuxing Yang, Nachuan Huang, Lingying Shi, Guodong Shi, Ling School of Electrical and Electronic Engineering Engineering Sensor selection Sparsity We study the problem of sensor selection for distributed systems, where a large number of sensors are located spatially in many different locations. Specifically, we consider both perfect and packet-dropping communication channels. While the original problem is NP-hard, by adopting a sparse design, we can solve the problem via convex optimization and reduce the computation cost significantly. Our method not only handles correlated measurement noise but also can be easily extended to actuator selection or sensor-and-actuator (SaA) selection problems. Simulation shows that our sparsity-based approach performs similarly to the brute force optimal strategy while consuming significantly less computation time. Additionally, our method is shown to outperform the state-of-art method notably. The work by Y. Zhong, N. Yang and L. Shi is supported by the Hong Kong RGC General Research Fund 16211622. 2024-07-23T04:46:29Z 2024-07-23T04:46:29Z 2024 Journal Article Zhong, Y., Yang, N., Huang, L., Shi, G. & Shi, L. (2024). Sparse sensor selection for distributed systems: an l1-relaxation approach. Automatica, 165, 111670-. https://dx.doi.org/10.1016/j.automatica.2024.111670 0005-1098 https://hdl.handle.net/10356/179227 10.1016/j.automatica.2024.111670 2-s2.0-85192179172 165 111670 en Automatica © 2024 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Sensor selection
Sparsity
spellingShingle Engineering
Sensor selection
Sparsity
Zhong, Yuxing
Yang, Nachuan
Huang, Lingying
Shi, Guodong
Shi, Ling
Sparse sensor selection for distributed systems: an l1-relaxation approach
description We study the problem of sensor selection for distributed systems, where a large number of sensors are located spatially in many different locations. Specifically, we consider both perfect and packet-dropping communication channels. While the original problem is NP-hard, by adopting a sparse design, we can solve the problem via convex optimization and reduce the computation cost significantly. Our method not only handles correlated measurement noise but also can be easily extended to actuator selection or sensor-and-actuator (SaA) selection problems. Simulation shows that our sparsity-based approach performs similarly to the brute force optimal strategy while consuming significantly less computation time. Additionally, our method is shown to outperform the state-of-art method notably.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Zhong, Yuxing
Yang, Nachuan
Huang, Lingying
Shi, Guodong
Shi, Ling
format Article
author Zhong, Yuxing
Yang, Nachuan
Huang, Lingying
Shi, Guodong
Shi, Ling
author_sort Zhong, Yuxing
title Sparse sensor selection for distributed systems: an l1-relaxation approach
title_short Sparse sensor selection for distributed systems: an l1-relaxation approach
title_full Sparse sensor selection for distributed systems: an l1-relaxation approach
title_fullStr Sparse sensor selection for distributed systems: an l1-relaxation approach
title_full_unstemmed Sparse sensor selection for distributed systems: an l1-relaxation approach
title_sort sparse sensor selection for distributed systems: an l1-relaxation approach
publishDate 2024
url https://hdl.handle.net/10356/179227
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