TY - JOUR
T1 - Dynamic event-triggered asynchronous filtering of Markovian jump systems against cyber-attacks
AU - Wang, Chunlian
AU - Xue, Fangzheng
AU - Su, Xiaojie
AU - Ma, Xiaoyu
AU - Ao, Wengang
AU - Minchala, Luis Ismael
N1 - Publisher Copyright:
© 2023
PY - 2024/2
Y1 - 2024/2
N2 - The paper focuses on the asynchronous filter design based on hidden Markovian model for Markovian jump systems with time-delay and external disturbances. Cyber nonlinearities in the communication environment are also considered. To further reduce the network bandwidth usage, an internal dynamic variable is introduced based on the previously extensively studied (static) event-triggered method, which is called dynamic event-triggered approach. The hidden Markovian model is utilized to characterize the asynchronous phenomenon caused by clock signals out of sync between system and filter mode. Then, according to the augmented filtering error system dynamics, some less conservative sufficient conditions are proposed to guarantee the stochastic stability with H∞ performance. Consecutively, the filter parameter-solving problem is synthesized by a convex optimization problem. Finally, two numerical simulations are presented to demonstrate the effectiveness of the proposed approach.
AB - The paper focuses on the asynchronous filter design based on hidden Markovian model for Markovian jump systems with time-delay and external disturbances. Cyber nonlinearities in the communication environment are also considered. To further reduce the network bandwidth usage, an internal dynamic variable is introduced based on the previously extensively studied (static) event-triggered method, which is called dynamic event-triggered approach. The hidden Markovian model is utilized to characterize the asynchronous phenomenon caused by clock signals out of sync between system and filter mode. Then, according to the augmented filtering error system dynamics, some less conservative sufficient conditions are proposed to guarantee the stochastic stability with H∞ performance. Consecutively, the filter parameter-solving problem is synthesized by a convex optimization problem. Finally, two numerical simulations are presented to demonstrate the effectiveness of the proposed approach.
KW - Dynamic event-triggered
KW - Hidden Markovian model
KW - Markovian jump systems
KW - ℋ asynchronous filtering
UR - https://www.scopus.com/pages/publications/85182507759
U2 - 10.1016/j.jfranklin.2023.12.007
DO - 10.1016/j.jfranklin.2023.12.007
M3 - Artículo
AN - SCOPUS:85182507759
SN - 0016-0032
VL - 361
SP - 1268
EP - 1283
JO - Journal of the Franklin Institute
JF - Journal of the Franklin Institute
IS - 3
ER -