Hybrid recurrent neural network for nonlinear hybrid dynamical systems identification

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

This paper is devoted to the development of a Neural Network Hybrid Identification Framework for unknown Nonlinear Hybrid Dynamical Systems. The proposal is based in the well known Recurrent Trainable Neural Networks Identifiers. In a first instance, the unknown hybrid system is considered like a black-box where by using only hybrid input-output data an approximated model is found. In a second instance, by considering that the hybrid output of the unknown hybrid system is triggered by a defined set of hypersurfaces we extent the approach identification by introducing a Hybrid Recurrent Trainable Neural Network Identifier. The effectiveness of the proposed approach is shown using a commutable pendulum example.

Idioma originalInglés
Título de la publicación alojadaCCE 2011 - 2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, Program and Abstract Book
DOI
EstadoPublicada - 2011
Evento2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2011 - Merida, Yucatan, México
Duración: 26 oct. 201128 oct. 2011

Serie de la publicación

NombreCCE 2011 - 2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, Program and Abstract Book

Conferencia

Conferencia2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2011
País/TerritorioMéxico
CiudadMerida, Yucatan
Período26/10/1128/10/11

Huella

Profundice en los temas de investigación de 'Hybrid recurrent neural network for nonlinear hybrid dynamical systems identification'. En conjunto forman una huella única.

Citar esto