Title :
Trajectory Tracking of Complex Dynamical Network for Delayed Recurrent Neural Network via Control V-Stability
Author :
Pérez, José P. ; Gonzalez, Jorge A. ; Soto, Rogelio ; Perez, Joel
Author_Institution :
Dept. of Phys. & Math. Sci., Autonomous Univ. of Nuevo Leon, Nuevo Leon, Mexico
fDate :
Sept. 28 2010-Oct. 1 2010
Abstract :
In this paper the problem of trajectory tracking is studied. Based on the V-stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results we present a tracking simulation of a dynamical network with each node being a Chen´s dynamical system.
Keywords :
Lyapunov methods; asymptotic stability; complex networks; position control; recurrent neural nets; Chen dynamical system; Lyapunov theory; complex dynamical network; control V-stability; control law; delayed recurrent neural network; global asymptotic stability; tracking error; tracking simulation; trajectory tracking; Artificial neural networks; Complex networks; Couplings; Recurrent neural networks; Stability analysis; Target tracking; Trajectory; Lyapunov analysis; Trajectory tracking; V-stability; complex dynamical network; delayed recurrent neural network;
Conference_Titel :
Electronics, Robotics and Automotive Mechanics Conference (CERMA), 2010
Conference_Location :
Morelos
Print_ISBN :
978-1-4244-8149-1
DOI :
10.1109/CERMA.2010.9
