IMPROVED RESULTS ON FINITE-TIME SYNCHRONIZATION OF SHUNTING INHIBITORY CELLULAR NEURAL NETWORKS WITH TIME-VARYING DELAYS VIA HYBRID IMPULSIVE PINNING CONTROL

Abstract

This thesis explores finite-time synchronization in shunting inhibitory cellular neural networks (SICNNs) with time-varying delays. An advanced hybrid controller is introduced to achieve this, serving as a state-feedback and pinning-impulsive controller during impulsive intervals and instants, respectively. Considering the basic Lyapunov function, the paper proposes finite-time synchronization for the SICNNs-based master-slave model structured along with the hybrid controller. This proposition is validated through a series of case studies highlighting the effectiveness of the hybrid controller. Furthermore, this paper compares the settling time of finite-time synchronization using the proposed hybrid controller against the classic state-feedback and pinning-impulsive controller, demonstrating the advantages of the hybrid approach. The effectiveness of the proposed hybrid controller is exemplified through a numerical example, showcasing consensus between MATLAB software simulations and manual computations. The comparison analysis includes assessing the proposed hybrid controller against the classic state-feedback and pinning-impulsive controllers.