Complex dynamical network control for trajectory tracking using delayed recurrent neural networks
Pérez Padrón, José Paz y Pérez Padrón, Joel y Flores Hernández, Ángel y Arroyo Garza, Santiago (2014) Complex dynamical network control for trajectory tracking using delayed recurrent neural networks. Mathematical Problems in Engineering, 2014. pp. 1-7. ISSN 1024-123X
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Resumen
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 just one Lorenz’s dynamical system and three identical Chen’s dynamical systems.
Tipo de elemento: | Article | |||||||||||||||
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Divisiones: | Ciencias Físico Matemáticas | |||||||||||||||
Usuario depositante: | Editor Repositorio | |||||||||||||||
Creadores: |
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Fecha del depósito: | 29 Mar 2019 18:45 | |||||||||||||||
Última modificación: | 20 Mayo 2021 14:55 | |||||||||||||||
URI: | http://eprints.uanl.mx/id/eprint/15144 |
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