TY - GEN
T1 - IT2FNN-Based Mode-Asynchrony Variable-Structure Control under Event-Triggered Communication
AU - Wang, Jiahui
AU - Zuo, Wen
AU - Gao, Yabin
AU - Liu, Jianxing
AU - Wu, Ligang
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper deals with the problem of mode-asynchrony sliding-mode variable-structure control (VSC) under event-triggered communication for continuous-time Markov jump systems with hidden modes. The hidden-mode Markov jump systems with both the matched and mismatched uncertainties are formulated. In terms of the event-triggered communication from the sensor to the controller, static and dynamic mechanisms based on periodic/aperiodic sampling are designed for mitigating the burden of communication. In this case of mode-asynchrony and aperiodic sampling state measurements, new sliding-mode VSC laws integrated with an interval type-2 fuzzy neural network are designed. The interval type-2 fuzzy neural network is used to approximate matched uncertainty. Moreover, the analysis of the finitetime practical stability of the control system is presented based on the Lyapunov function approach. Finally, a set of simulation results are given to show the validity and practicability of the present results.
AB - This paper deals with the problem of mode-asynchrony sliding-mode variable-structure control (VSC) under event-triggered communication for continuous-time Markov jump systems with hidden modes. The hidden-mode Markov jump systems with both the matched and mismatched uncertainties are formulated. In terms of the event-triggered communication from the sensor to the controller, static and dynamic mechanisms based on periodic/aperiodic sampling are designed for mitigating the burden of communication. In this case of mode-asynchrony and aperiodic sampling state measurements, new sliding-mode VSC laws integrated with an interval type-2 fuzzy neural network are designed. The interval type-2 fuzzy neural network is used to approximate matched uncertainty. Moreover, the analysis of the finitetime practical stability of the control system is presented based on the Lyapunov function approach. Finally, a set of simulation results are given to show the validity and practicability of the present results.
KW - Markov jump systems
KW - asynchronous control
KW - dynamic event-triggered communication
KW - fuzzy neural network
KW - variable-structure control
UR - https://www.scopus.com/pages/publications/85149519845
U2 - 10.1109/CCDC55256.2022.10033678
DO - 10.1109/CCDC55256.2022.10033678
M3 - 会议稿件
AN - SCOPUS:85149519845
T3 - Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022
SP - 4600
EP - 4605
BT - Proceedings of the 34th Chinese Control and Decision Conference, CCDC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 34th Chinese Control and Decision Conference, CCDC 2022
Y2 - 15 August 2022 through 17 August 2022
ER -