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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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. |
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Engineering Sensor selection Sparsity Zhong, Yuxing Yang, Nachuan Huang, Lingying Shi, Guodong Shi, Ling Sparse sensor selection for distributed systems: an l1-relaxation approach |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Zhong, Yuxing Yang, Nachuan Huang, Lingying Shi, Guodong Shi, Ling |
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Article |
author |
Zhong, Yuxing Yang, Nachuan Huang, Lingying Shi, Guodong Shi, Ling |
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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 |
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Sparse sensor selection for distributed systems: an l1-relaxation approach |
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sparse sensor selection for distributed systems: an l1-relaxation approach |
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2024 |
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https://hdl.handle.net/10356/179227 |
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1806059892828536832 |