Adaptive architectures for resilient control of networked multiagent systems in the presence of misbehaving agents
Control algorithms of networked multiagent systems are generally computed distributively without having a centralised entity monitoring the activity of agents; and therefore, unforeseen adverse conditions such as uncertainties or attacks to the communication network and/or failure of agent-wise comp...
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| Veröffentlicht in: | International journal of control Jg. 91; H. 3; S. 495 - 507 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Abingdon
Taylor & Francis
04.03.2018
Taylor & Francis Ltd |
| Schlagworte: | |
| ISSN: | 0020-7179, 1366-5820 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | Control algorithms of networked multiagent systems are generally computed distributively without having a centralised entity monitoring the activity of agents; and therefore, unforeseen adverse conditions such as uncertainties or attacks to the communication network and/or failure of agent-wise components can easily result in system instability and prohibit the accomplishment of system-level objectives. In this paper, we study resilient coordination of networked multiagent systems in the presence of misbehaving agents, i.e. agents that are subject to exogenous disturbances that represent a class of adverse conditions. In particular, a distributed adaptive control architecture is presented for directed and time-varying graph topologies to retrieve a desired networked multiagent system behaviour. Apart from the existing relevant literature that make specific assumptions on the graph topology and/or the fraction of misbehaving agents, we show that the considered class of adverse conditions can be mitigated by the proposed adaptive control approach that utilises a local state emulator - even if all agents are misbehaving. Illustrative numerical examples are provided to demonstrate the theoretical findings. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0020-7179 1366-5820 |
| DOI: | 10.1080/00207179.2017.1286040 |