FINITE-TIME OUTPUT-FEEDBACK PASSIFICATION OF UNCERTAIN FRACTIONAL-ORDER NEURAL NETWORKS HAVING TIME-VARYING DELAYS

Abstract

The purpose of the study was to investigate the finite-time stability and output feedback finite-time passification of fractional order uncertain neural networks with time-varying delay. We derived conditions for finite-time boundedness and finite-time passivity using linear matrix inequality, Lyapunov functional, and Schur complement Lemma we reached finite-time stability of the system. Certainly derivation and integration for fractional order calculus, that we used for neural network system, differs from conventional integer order calculus, by its hereditary characteristics. The findings have substantial implications for the design and control of complex neural network systems, paving the way for improved robustness and reliability in real-world applications.