Distributed consensus-based multitarget filtering and its application in formation-containment control

This paper studies a distributed multitarget filtering problem for a sensor network where each sensor can obtain the measurements and system information of some targets while having no knowledge of others. To estimate the states of all targets, a consensus Kalman information filtering algorithm with...

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Main Authors: Zhang, Y., Sun, L., Hu, Guoqiang
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/154201
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1542012021-12-31T13:51:19Z Distributed consensus-based multitarget filtering and its application in formation-containment control Zhang, Y. Sun, L. Hu, Guoqiang School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Containment Control Distributed Filtering This paper studies a distributed multitarget filtering problem for a sensor network where each sensor can obtain the measurements and system information of some targets while having no knowledge of others. To estimate the states of all targets, a consensus Kalman information filtering algorithm with an adaptive and finite-time matrix-weighted consensus strategy is proposed. When the communication network is strongly connected and the sensing network is time-varying while being always collectively observable, it is proved that if the targets' system matrices are time invariant, the mean-square estimation errors of the sensors are bounded for any number of consensus iterations. If the targets' system matrices are time varying and the number of the consensus steps per information filtering is larger than the diameter of the communication topology, the mean-square estimation errors of the sensors are also bounded. When each sensor is intermittently activated to observe the targets and the network does not remain collectively observable, an allowable lower bound of detection probability is derived to guarantee the stochastic boundedness of the estimation errors. Then, the filtering algorithm is applied to design a distributed containment controller for multiple agents to encircle multiple planar heterogeneous dynamic targets. Finally, simulation examples are given to illustrate the effectiveness of the algorithms. Ministry of Education (MOE) This work was supported in part by the National Natural Science Foundation (NNSF) of China under Grant 61473081, in part by the Six Talent Peaks Project in Jiangsu Province under Grant XYDXX-005, and in part by the Singapore Ministry of Education Academic Research Fund Tier 1 RG180/17(2017-T1-002- 158). Recommended by Associate Editor L. Schenato. 2021-12-16T02:38:58Z 2021-12-16T02:38:58Z 2020 Journal Article Zhang, Y., Sun, L. & Hu, G. (2020). Distributed consensus-based multitarget filtering and its application in formation-containment control. IEEE Transactions On Control of Network Systems, 7(1), 503-515. https://dx.doi.org/10.1109/TCNS.2019.2926281 2325-5870 https://hdl.handle.net/10356/154201 10.1109/TCNS.2019.2926281 2-s2.0-85068542593 1 7 503 515 en RG180/17(2017-T1-002- 158) IEEE Transactions on Control of Network Systems © 2019 IEEE. 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::Electrical and electronic engineering
Containment Control
Distributed Filtering
spellingShingle Engineering::Electrical and electronic engineering
Containment Control
Distributed Filtering
Zhang, Y.
Sun, L.
Hu, Guoqiang
Distributed consensus-based multitarget filtering and its application in formation-containment control
description This paper studies a distributed multitarget filtering problem for a sensor network where each sensor can obtain the measurements and system information of some targets while having no knowledge of others. To estimate the states of all targets, a consensus Kalman information filtering algorithm with an adaptive and finite-time matrix-weighted consensus strategy is proposed. When the communication network is strongly connected and the sensing network is time-varying while being always collectively observable, it is proved that if the targets' system matrices are time invariant, the mean-square estimation errors of the sensors are bounded for any number of consensus iterations. If the targets' system matrices are time varying and the number of the consensus steps per information filtering is larger than the diameter of the communication topology, the mean-square estimation errors of the sensors are also bounded. When each sensor is intermittently activated to observe the targets and the network does not remain collectively observable, an allowable lower bound of detection probability is derived to guarantee the stochastic boundedness of the estimation errors. Then, the filtering algorithm is applied to design a distributed containment controller for multiple agents to encircle multiple planar heterogeneous dynamic targets. Finally, simulation examples are given to illustrate the effectiveness of the algorithms.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Zhang, Y.
Sun, L.
Hu, Guoqiang
format Article
author Zhang, Y.
Sun, L.
Hu, Guoqiang
author_sort Zhang, Y.
title Distributed consensus-based multitarget filtering and its application in formation-containment control
title_short Distributed consensus-based multitarget filtering and its application in formation-containment control
title_full Distributed consensus-based multitarget filtering and its application in formation-containment control
title_fullStr Distributed consensus-based multitarget filtering and its application in formation-containment control
title_full_unstemmed Distributed consensus-based multitarget filtering and its application in formation-containment control
title_sort distributed consensus-based multitarget filtering and its application in formation-containment control
publishDate 2021
url https://hdl.handle.net/10356/154201
_version_ 1722355346028101632