Finite-Time and Fixed-Time Synchronization of Coupled Switched Neural Networks Subject to Stochastic Disturbances

• Published in: IEEE transactions on systems, man, and cybernetics. Systems Vol. 52; no. 10; pp. 6511 - 6523
• Main Authors: Guo, Zhenyuan, Xie, Hui, Wang, Jun
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Control theory; Couplings; Disturbances; Dynamical systems; Finite/fixed-time synchronization; Markovian switching; Neural networks; Oscillators; Settling; state-dependent switching; stochastic disturbances; switched neural networks (SNNs); Switches; Switching; Synchronization; Time synchronization; Topology; Upper bound; Upper bounds
• ISSN: 2168-2216; 2168-2232
• DOI: 10.1109/TSMC.2022.3146892

In this paper, we address the finite-time and fixed-time synchronization of a general class of switched neural networks (SNNs) with time delays subject to stochastic disturbances. Considering two types of switching in this class of SNNs: 1) intra-SNN state-dependent switching and 2) inter-SNN Markovian switching, we develop three control laws and derive three sets of sufficient conditions for both finite-time and fixed-time synchronization of SNNs subject to stochastic disturbances. We make two remarks on the effects of control-law parameters on synchronization settling time. Moreover, we derive several upper bounds of synchronization settling time and evaluate their pros and cons. Finally, we elaborate on two numerical examples to illustrate the viability of the theoretical results.