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Decentralised finite‐time consensus for second‐order multi‐agent system under event‐triggered strategy
Author(s) -
Zhang Liang,
Zhang Zexu,
Lawrance Nicholas,
Nieto Juan,
Siegwart Roland
Publication year - 2020
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2019.0865
Subject(s) - control theory (sociology) , correctness , computer science , consensus , actuator , multi agent system , controller (irrigation) , protocol (science) , graph , control (management) , algorithm , artificial intelligence , theoretical computer science , medicine , alternative medicine , pathology , agronomy , biology
In this technical note, the authors address the finite‐time consensus problem of a second‐order multi‐agent system (SOMAS) under an event‐triggered control strategy. This problem arises from the case where actuators in a SOMAS fail to follow the ideal controller behaviour exactly, due to either the failure of an embedded processor to maintain the desired update rate or a large time constant in the actuators, while still trying to maintain some performance merits from the finite‐time control theory. A decentralised event‐triggered non‐linear protocol is proposed based on only local information for the undirected and connected communication graph. The rigorous proof is then presented and shows that the consensus can be achieved in finite time even under event‐triggered schemes. Owing to the event‐triggered strategy, they proposed a technique that bounds the steady errors of agent states into a small region around zero in finite time and reduces the update frequency of actuators while excluding the Zeno behaviour. Finally, simulation results are provided to validate the correctness and effectiveness of the proposed method and demonstrate that it can adjust a composed performance metrics with respect to the convergent rate, consensus accuracy, and update frequency of actuators by tuning the parameters in the control protocol.

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