Resumen

PEREZ PADRON, J.; PEREZ PADRON, J.P.; MENDEZ-BARRIOS, C.F.  y  GONZALEZ-GALVAN, E.J.. Trajectory tracking error using fractional order time-delay recurrent neural networks using Krasovskii-Lur’e functional for Chua’s circuit via inverse optimal control. Rev. mex. fis. [online]. 2020, vol.66, n.1, pp.98-104.  Epub 27-Nov-2020. ISSN 0035-001X.  https://doi.org/10.31349/revmexfis.66.98.

This paper presents an application of a Fractional-Order Time Delay Neural Networks to chaos synchronization. The two main methodologies, on which the approach is based, are fractional-order time-delay recurrent neural networks and the fractional-order inverse optimal control for nonlinear systems. The problem of trajectory tracking is studied, based on the fractional-order Lyapunov-Krasovskii and Lur’e theory, that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a reference function is obtained. The method is illustrated for the synchronization, the analytic results we present a trajectory tracking simulation of a fractional-order time-delay dynamical network and the Fractional Order Chua’s circuits.

Palabras llave : Trajectory tracking; fractional order time-delay recurrent neural network; fractional order Lyapunov-Krasovskii and Lur’e analysis.