Resilient self/event-triggered consensus based on ternary control
2021
Abstract This paper considers the problem of multi-agent consensus in the presence of adversarial agents. Such adversaries may try to introduce undesired influence on the coordination of the regular agents and to even prevent them from reaching consensus. To our setting, we extend the so-called mean subsequence reduced algorithms with the aim to reduce the use of computation and communication resources of the agents. In particular, by employing self- and event-triggered communication, the frequencies of state updates as well as data transmissions are kept low. Moreover, the control inputs of the agents take the form of ternary signals, allowing them to further reduce the amount of information at each transmission. We will observe that in hostile environments with adversaries, the self-triggered approach can bring certain advantages over the event-triggered counterpart. Moreover, a novel switching scheme is introduced to mix the two protocols to further enhance the performance of the agents.
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