Proceedings of the 2019 2nd International Conference on Mathematics, Modeling and Simulation Technologies and Applications (MMSTA 2019)

Consensus Analysis of Continuous-time Multi-agent Systems with Semi-Markov Switching Topologies

Authors
Guoliang Wang, Yuanyuan Sun
Corresponding Author
Guoliang Wang
Available Online December 2019.
DOI
10.2991/mmsta-19.2019.46How to use a DOI?
Keywords
semi-Markov (SM) switching topologies; Markovian jump system (MJS); consensus; multi-agent system (MAS)
Abstract

The consensus problem about continuous time multi-agent system (MAS) with semi-Markov (SM) switching topologies is studied in this paper. Switching topology whose sojourn-times satisfy a general probability distribution is a general Markov renewal process. The problem about consensus is considered that constructing a discrete-time Markovian jump system (MJS) with sojourn-time bounds and transition probabilities bounds. Then, it presented novel test conditions with easily solvable forms. Finally, an example is given to verify the proposed method available.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2019 2nd International Conference on Mathematics, Modeling and Simulation Technologies and Applications (MMSTA 2019)
Series
Advances in Computer Science Research
Publication Date
December 2019
ISBN
10.2991/mmsta-19.2019.46
ISSN
2352-538X
DOI
10.2991/mmsta-19.2019.46How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Guoliang Wang
AU  - Yuanyuan Sun
PY  - 2019/12
DA  - 2019/12
TI  - Consensus Analysis of Continuous-time Multi-agent Systems with Semi-Markov Switching Topologies
BT  - Proceedings of the 2019 2nd International Conference on Mathematics, Modeling and Simulation Technologies and Applications (MMSTA 2019)
PB  - Atlantis Press
SP  - 217
EP  - 220
SN  - 2352-538X
UR  - https://doi.org/10.2991/mmsta-19.2019.46
DO  - 10.2991/mmsta-19.2019.46
ID  - Wang2019/12
ER  -