A distributed resilient control strategy for leader-follower systems under replay attacks

Abstract

In this paper, we present a novel resilient control architecture capable to manage replay attacks for multi-agent discrete-time linear systems subject to input and state constraints. By considering a leader-follower configuration, the basic idea consists of exploiting model predictive control arguments to apply adequate control action in order to isolate the attacked unit that otherwise could compromise system operations. To this end, a set-theoretic receding horizon control strategy is developed that is also capable to instantaneously detect the attacked agent along the platoon chain. Finally, we describe a set of simulations on a group of mobile robots to demonstrate the effectiveness of the proposed approach.