Document Type
Article
Publication Date
12-2020
Department
Engineering
Keywords
protocols, stability analysis, safety, asymptotic stability, resilience, power system stability, decentralized control
Abstract
Decentralized control systems are widely used in a number of situations and applications. In order for these systems to function properly and achieve their desired goals, information must be propagated between agents. However, communication between agents entails connecting to a network, potentially allowing adversaries to infiltrate the system through the network and attack multiple agents. To increase resiliency against these attacks, it is desirable for agents to operate disconnected from the network as much as possible, only communicating with other agents when it is absolutely necessary to achieve their goal or to maintain the safety of the overall system. This in turn decreases communication costs. Previous approaches to decentralized event-triggered control are mainly concerned with minimizing communication costs and therefore assume that every agent is always connected to the network with the ability to receive any information that is sent to it. In this work, we address the issue of maintaining the safety and stability of the overall system when there is no attack but some agents may be disconnected from the network and unable to receive critical information from other agents. We design an event-triggered mechanism for network connection and communication that is a function of only local information and that ensures stability for the overall system in attack-free scenarios. An algorithm describing this communication protocol is provided, and our approach is illustrated via simulation.
Source Publication Title
2020 59th IEEE Conference on Decision and Control
Publisher
IEEE
First Page
3236
DOI
10.1109/CDC42340.2020.9303888
Recommended Citation
Griffioen, P., Romagnoli, R., Krogh, B. H., & Sinopoli, B. (2020). Decentralized Event-Triggered Control in the Presence of Adversaries. 2020 59th IEEE Conference on Decision and Control, 3236. https://doi.org/10.1109/CDC42340.2020.9303888
Comments
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