TY - GEN
T1 - Distributed Event-Triggered Consensus Control from Noisy Data Using Matrix Polytopes
AU - Li, Yifei
AU - Liu, Wenjie
AU - Sun, Jian
AU - Wang, Gang
AU - Chen, Jie
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper presents a novel data-driven polytopic approach to event-triggered consensus control of unknown leader-following multi-agent systems (MASs). A distributed data-driven event-triggered consensus control protocol is proposed that utilizes noisy input-state data to enable all followers to track the leader while reducing communication and computational burden. Unlike previous research that relies on quadratic matrix inequalities to characterize system uncertainties, this paper devises a data-based polytopic representation for MASs, which enables addressing the consensus control problem without using explicit system matrices. Based on this representation, a data-based criterion is established, utilizing matrix polytopes to ensure the asymptotic stability of the closed-loop MAS. Moreover, a co-design method is presented for the distributed controller gain and the triggering matrix, using only data and expressed in terms of linear matrix inequalities. Finally, numerical simulations are conducted to demonstrate the validity and effectiveness of the proposed data-driven approach.
AB - This paper presents a novel data-driven polytopic approach to event-triggered consensus control of unknown leader-following multi-agent systems (MASs). A distributed data-driven event-triggered consensus control protocol is proposed that utilizes noisy input-state data to enable all followers to track the leader while reducing communication and computational burden. Unlike previous research that relies on quadratic matrix inequalities to characterize system uncertainties, this paper devises a data-based polytopic representation for MASs, which enables addressing the consensus control problem without using explicit system matrices. Based on this representation, a data-based criterion is established, utilizing matrix polytopes to ensure the asymptotic stability of the closed-loop MAS. Moreover, a co-design method is presented for the distributed controller gain and the triggering matrix, using only data and expressed in terms of linear matrix inequalities. Finally, numerical simulations are conducted to demonstrate the validity and effectiveness of the proposed data-driven approach.
UR - http://www.scopus.com/inward/record.url?scp=85184805031&partnerID=8YFLogxK
U2 - 10.1109/CDC49753.2023.10384237
DO - 10.1109/CDC49753.2023.10384237
M3 - Conference contribution
AN - SCOPUS:85184805031
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 1607
EP - 1612
BT - 2023 62nd IEEE Conference on Decision and Control, CDC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 62nd IEEE Conference on Decision and Control, CDC 2023
Y2 - 13 December 2023 through 15 December 2023
ER -