Synchronization of Fractional-Order Delayed Neural Networks Using Dynamic-Free Adaptive Sliding Mode Control

In this work, a dynamic-free adaptive sliding mode control (adaptive-SMC) methodology for the synchronization of specific class chaotic delayed fractional-order neural network systems in presence input saturation is proposed. By incorporating frequency distributed model (FDM) and fractional version Lyapunov stability theory, SMC designed to effectively overcome inherent behavior exhibited by FONNSs achieve synchronization. Notably, decoupling laws from nonlinear/linear dynamical components system ensured, taking advantage norm-boundedness property states systems. The effectiveness suggested adaptive-SMC method chaos Hopfield validated through numerical simulations, demonstrating its robustness efficiency. proposed approach, FDM theorem, offers promising solution synchronizing with saturation, potential applications various domains requiring such