Fractional Complex Dynamical Systems for Trajectory Tracking using Fractional Neural Network
In this paper the problem of trajectory tracking is studied. Based on Lyapunov theory, a control law that achieves global asymptotic stability of the tracking error between a fractional recurrent neural network and the state of each single node of the fractional complex dynamical network is obtained...
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | México |
| Institución: | Universidad Autónoma de Nuevo León |
| Repositorio: | Redalyc-UANL |
| OAI Identifier: | oai:redalyc.org:61547018005 |
| Acceso en línea: | https://www.redalyc.org/articulo.oa?id=61547018005 |
| Access Level: | acceso abierto |
| Palabra clave: | Computación control law Lyapunov theory trajectory tracking Fractional complex dynamical systems |
| Sumario: | In this paper the problem of trajectory tracking is studied. Based on Lyapunov theory, a control law that achieves global asymptotic stability of the tracking error between a fractional recurrent neural network and the state of each single node of the fractional complex dynamical network is obtained. To illustrate the analytic results we present a tracking simulation of a simple network with four different nodes and five non-uniform links. |
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