Please use this identifier to cite or link to this item: http://localhost:80/handle/Hannan/154786
Title: Robust consensus for linear multi-agent systems with noises
Authors: Zhongmei Wang;Wei Wang;Huanshui Zhang
subject: agent state estimation|communication noises|Lyapunov equation|system noises|robust consensus problem|linear multiagent systems|consensus protocol|noisy measurement information|MAS|neighbour agents|Kalman-filtering theory|consensusability|relative estimated state|noisy communication environment|consensus error|dynamic output feedback control
Year: 2016
Publisher: IEEE
Abstract: This study investigates robust consensus problem for multi-agent systems (MASs) with both system and communication noises. The agent state is estimated based on the noisy measurement information by applying Kalman-filtering theory, and then the estimated state is sent to the neighbour agents through a noisy communication environment. A consensus protocol is proposed based on the relative estimated state, under which the consensus error of the MASs can be characterised precisely via the unique solution of a Lyapunov equation. In addition, the consensusability via dynamic output feedback control of the MASs without noises is studied. Finally, simulation examples are given to show the correctness of the proposed results.
URI: http://localhost/handle/Hannan/154786
ISSN: 1751-8644
1751-8652
volume: 10
issue: 17
More Information: 2348
2356
Appears in Collections:2016

Files in This Item:
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Title: Robust consensus for linear multi-agent systems with noises
Authors: Zhongmei Wang;Wei Wang;Huanshui Zhang
subject: agent state estimation|communication noises|Lyapunov equation|system noises|robust consensus problem|linear multiagent systems|consensus protocol|noisy measurement information|MAS|neighbour agents|Kalman-filtering theory|consensusability|relative estimated state|noisy communication environment|consensus error|dynamic output feedback control
Year: 2016
Publisher: IEEE
Abstract: This study investigates robust consensus problem for multi-agent systems (MASs) with both system and communication noises. The agent state is estimated based on the noisy measurement information by applying Kalman-filtering theory, and then the estimated state is sent to the neighbour agents through a noisy communication environment. A consensus protocol is proposed based on the relative estimated state, under which the consensus error of the MASs can be characterised precisely via the unique solution of a Lyapunov equation. In addition, the consensusability via dynamic output feedback control of the MASs without noises is studied. Finally, simulation examples are given to show the correctness of the proposed results.
URI: http://localhost/handle/Hannan/154786
ISSN: 1751-8644
1751-8652
volume: 10
issue: 17
More Information: 2348
2356
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7740199.pdf1.82 MBAdobe PDFThumbnail
Preview File
Title: Robust consensus for linear multi-agent systems with noises
Authors: Zhongmei Wang;Wei Wang;Huanshui Zhang
subject: agent state estimation|communication noises|Lyapunov equation|system noises|robust consensus problem|linear multiagent systems|consensus protocol|noisy measurement information|MAS|neighbour agents|Kalman-filtering theory|consensusability|relative estimated state|noisy communication environment|consensus error|dynamic output feedback control
Year: 2016
Publisher: IEEE
Abstract: This study investigates robust consensus problem for multi-agent systems (MASs) with both system and communication noises. The agent state is estimated based on the noisy measurement information by applying Kalman-filtering theory, and then the estimated state is sent to the neighbour agents through a noisy communication environment. A consensus protocol is proposed based on the relative estimated state, under which the consensus error of the MASs can be characterised precisely via the unique solution of a Lyapunov equation. In addition, the consensusability via dynamic output feedback control of the MASs without noises is studied. Finally, simulation examples are given to show the correctness of the proposed results.
URI: http://localhost/handle/Hannan/154786
ISSN: 1751-8644
1751-8652
volume: 10
issue: 17
More Information: 2348
2356
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7740199.pdf1.82 MBAdobe PDFThumbnail
Preview File