Trajectory tracking error using fractional order time-delay recurrent neural networks using Krasovskii-Lur’e functional for Chua’s circuit via inverse optimal control
Abstract 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.
| Main Authors: | , , , |
|---|---|
| Format: | Digital revista |
| Language: | English |
| Published: |
Sociedad Mexicana de Física
2020
|
| Online Access: | http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S0035-001X2020000100098 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|