TY - GEN
T1 - Event-triggered adaptive compensation control for nonlinear cyber-physical systems under false data injection attacks
AU - Wang, Pengbiao
AU - Ren, Xuemei
AU - Zheng, Dongdong
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - In this paper, we study the event-triggered adaptive compensate control problem for cyber-physical systems constructed by nonlinear systems with unknown parameters under false data injection attacks. First, a new adaptive event-triggered scheme (AETS) is designed to save limited network resources, and its threshold can be continuously adjusted according to the change of system state. In particular, the proposed adaptive event-triggered scheme can degenerate into the existing event-triggered scheme with the fixed threshold. Then, an adaptive controller and adaptive laws are designed to effectively compensate for false data injection attacks. Furthermore, it is proved that the tracking error of the system can be exponentially converged within a compact set with an adjustable radius. Finally, a simulation example shows the effectiveness of the proposed method.
AB - In this paper, we study the event-triggered adaptive compensate control problem for cyber-physical systems constructed by nonlinear systems with unknown parameters under false data injection attacks. First, a new adaptive event-triggered scheme (AETS) is designed to save limited network resources, and its threshold can be continuously adjusted according to the change of system state. In particular, the proposed adaptive event-triggered scheme can degenerate into the existing event-triggered scheme with the fixed threshold. Then, an adaptive controller and adaptive laws are designed to effectively compensate for false data injection attacks. Furthermore, it is proved that the tracking error of the system can be exponentially converged within a compact set with an adjustable radius. Finally, a simulation example shows the effectiveness of the proposed method.
KW - Cyber-physical systems
KW - adaptive compensation control
KW - adaptive event-triggered scheme
KW - false data injection attacks
UR - http://www.scopus.com/inward/record.url?scp=85125204833&partnerID=8YFLogxK
U2 - 10.1109/CCDC52312.2021.9602783
DO - 10.1109/CCDC52312.2021.9602783
M3 - Conference contribution
AN - SCOPUS:85125204833
T3 - Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021
SP - 702
EP - 707
BT - Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd Chinese Control and Decision Conference, CCDC 2021
Y2 - 22 May 2021 through 24 May 2021
ER -