Trajectory tracking for the chaotic pendulum using PI control law
This paper presents the application of trajectory tracking using adaptive neural networks to the double chaotic pendulum. The controller structure proposed is composed by a neural identifier and a PI Control Law. Experimental results with the chaotic pendulum showed the usefulness of the proposed ap...
| Autores: | , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | México |
| Recursos: | Universidad Autónoma de Nuevo León |
| Repositorio: | Redalyc-UANL |
| OAI Identifier: | oai:redalyc.org:57028305010 |
| Acesso em linha: | https://www.redalyc.org/articulo.oa?id=57028305010 |
| Access Level: | acceso abierto |
| Palavra-chave: | Física, Astronomía y Matemáticas Neural networks adaptive control trajectory tracking Lyapunov function stability and PI control |
| Resumo: | This paper presents the application of trajectory tracking using adaptive neural networks to the double chaotic pendulum. The controller structure proposed is composed by a neural identifier and a PI Control Law. Experimental results with the chaotic pendulum showed the usefulness of the proposed approach. To verify the analytical results, an example of a dynamical network is simulated and a theorem is proposed to ensure the tracking of the nonlinear system. |
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