Abstract
The performance in output synchronization in multi-agent systems (MAS) can degrade in the presence of misbehaving agents that are affected by external attacker actions that try to desynchronize the system. In this paper, we introduce a heuristic algorithm based on best-response games to define an online distributed reconfiguration strategy to dynamically mitigate these actions, to make the system reach a synchronization state. This algorithm provides each unattacked agent with a decision-making based on local information to reconfigure the interaction patterns with its neighbors such that the system eventually synchronizes. We present some simulations of the proposed strategy for several systems in realistic scenarios to show ability of the of the proposed algorithm to mitigate different types of attacks.
Highlights
The study of distributed control systems has become a relevant topic in control engineering
We introduced a heuristic algorithm based on a best-response game for attack mitigation in which every unattacked agent in the network dynamically changes its weights to achieve a synchronization state
We presented some simulations of the proposed mitigation strategy implemented on several systems that we considered provided a wide variety of scenarios
Summary
The study of distributed control systems has become a relevant topic in control engineering. All the aforementioned algorithms share an important characteristic: they mitigate the effect of misbehaving agents over a network by changing the connections of the topology of the communication graph, preserving the predefined control algorithm. Our contribution in this paper is an heuristic mechanism for resilient synchronization based on best-response games, which allows every agent in the network to reconfigure the communication links with its neighbors, preserving the distributed property of synchronization algorithms, and that works for a more extensive assortment of nonlinear synchronization control protocols under mild assumptions on the network topology. These algorithms allow for reconfiguration through changes in the communication topology used by the system, which is an important property for the proposed strategy. The parameters of this family of control algorithms affect how the agents synchronize, in future sections we assume that the control strategy is properly designed, i.e., the chosen χ(·) guarantees synchronization for all agents in the absence of an attack
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