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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Vydáno v:International journal of control Ročník 91; číslo 3; s. 495 - 507
Hlavní autoři: Torre, Gerardo De La, Yucelen, Tansel
Médium: Journal Article
Jazyk:angličtina
Vydáno: Abingdon Taylor & Francis 04.03.2018
Taylor & Francis Ltd
Témata:
Adaptive control
Cybersecurity
directed and time-varying graph topologies
distributed control
Multiagent systems
Networked multiagent systems
resilient control
Stability
stability analysis
Topology
ISSN:0020-7179, 1366-5820
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Shrnutí: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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ISSN:0020-7179
1366-5820
DOI:10.1080/00207179.2017.1286040