TY - JOUR
T1 - Exponential synchronization of reaction-diffusion neural networks via switched event-triggered control
AU - Zhang, Chuan
AU - Wu, Huaining
AU - Han, Xiang
AU - Zhang, Xianfu
N1 - Publisher Copyright:
© 2023 Elsevier Inc.
PY - 2023/11
Y1 - 2023/11
N2 - A switched event-triggered strategy for the synchronization control of reaction-diffusion neural networks (RDNNs) is developed, and the trigger condition is constructed by utilizing spatial information in the domain. First, a waiting time with regard to the event-triggered mechanism is implemented to avoid the Zeno phenomenon, under which the synchronization error system is converted to a switching system. Then, using the Lyapunov function, the Poincare's inequality and the free weighting matrix method, a sufficient condition for the exponential synchronization of RDNNs is given. Subsequently, an event-triggered controller is designed by virtue of the linear matrix inequalities. This method is also extended to deal with the synchronization of uncertain RDNNs. Finally, simulation examples illustrate our results.
AB - A switched event-triggered strategy for the synchronization control of reaction-diffusion neural networks (RDNNs) is developed, and the trigger condition is constructed by utilizing spatial information in the domain. First, a waiting time with regard to the event-triggered mechanism is implemented to avoid the Zeno phenomenon, under which the synchronization error system is converted to a switching system. Then, using the Lyapunov function, the Poincare's inequality and the free weighting matrix method, a sufficient condition for the exponential synchronization of RDNNs is given. Subsequently, an event-triggered controller is designed by virtue of the linear matrix inequalities. This method is also extended to deal with the synchronization of uncertain RDNNs. Finally, simulation examples illustrate our results.
KW - Reaction-diffusion neural networks
KW - Switched event-triggered control
KW - Synchronization
UR - https://www.scopus.com/pages/publications/85169811138
U2 - 10.1016/j.ins.2023.119599
DO - 10.1016/j.ins.2023.119599
M3 - 文章
AN - SCOPUS:85169811138
SN - 0020-0255
VL - 648
JO - Information Sciences
JF - Information Sciences
M1 - 119599
ER -