Robust identification of uncertain nonlinear systems with state constrains by Differential Neural Networks

Alejando García; Isaac Chairez; Alexander Poznyak; Tatyana Poznyak

doi:10.1109/IJCNN.2009.5178825

Robust identification of uncertain nonlinear systems with state constrains by Differential Neural Networks

Alejando García, Isaac Chairez, Alexander Poznyak, Tatyana Poznyak

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

2 Citas (Scopus)

Resumen

Non parametric identifier based on Differential Neural Networks is presented. Nonlinear systems with the a priori information about state constrains are considered. Differential Neural Network Identifier includes a projectional operator as part of its structure in order to keep the state restrictions. Stability Analysis based on Lyapunov-Krasovskii energetic-function lets proof the ultimated boundedness of error estimation. Free parameters stability of DNNI (Adaptive Weights) is also proved. Simulation examples regarding to biotechnological process and the Chua's circuit depict the main advantages of the proposed structure against reported Differential Neural Network with similar structure but without projectional operator.

Idioma original	Inglés
Título de la publicación alojada	2009 International Joint Conference on Neural Networks, IJCNN 2009
Páginas	917-924
Número de páginas	8
DOI	https://doi.org/10.1109/IJCNN.2009.5178825
Estado	Publicada - 2009
Publicado de forma externa	Sí
Evento	2009 International Joint Conference on Neural Networks, IJCNN 2009 - Atlanta, GA, Estados Unidos Duración: 14 jun. 2009 → 19 jun. 2009

Serie de la publicación

Nombre	Proceedings of the International Joint Conference on Neural Networks

Conferencia

Conferencia	2009 International Joint Conference on Neural Networks, IJCNN 2009
País/Territorio	Estados Unidos
Ciudad	Atlanta, GA
Período	14/06/09 → 19/06/09

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10.1109/IJCNN.2009.5178825

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García, A., Chairez, I., Poznyak, A., & Poznyak, T. (2009). Robust identification of uncertain nonlinear systems with state constrains by Differential Neural Networks. En 2009 International Joint Conference on Neural Networks, IJCNN 2009 (pp. 917-924). Artículo 5178825 (Proceedings of the International Joint Conference on Neural Networks). https://doi.org/10.1109/IJCNN.2009.5178825

@inproceedings{3a295f1b65a94dba82cd2ce54cec3955,

title = "Robust identification of uncertain nonlinear systems with state constrains by Differential Neural Networks",

abstract = "Non parametric identifier based on Differential Neural Networks is presented. Nonlinear systems with the a priori information about state constrains are considered. Differential Neural Network Identifier includes a projectional operator as part of its structure in order to keep the state restrictions. Stability Analysis based on Lyapunov-Krasovskii energetic-function lets proof the ultimated boundedness of error estimation. Free parameters stability of DNNI (Adaptive Weights) is also proved. Simulation examples regarding to biotechnological process and the Chua's circuit depict the main advantages of the proposed structure against reported Differential Neural Network with similar structure but without projectional operator.",

author = "Alejando Garc{\'i}a and Isaac Chairez and Alexander Poznyak and Tatyana Poznyak",

year = "2009",

doi = "10.1109/IJCNN.2009.5178825",

language = "Ingl{\'e}s",

isbn = "9781424435531",

series = "Proceedings of the International Joint Conference on Neural Networks",

pages = "917--924",

booktitle = "2009 International Joint Conference on Neural Networks, IJCNN 2009",

note = "2009 International Joint Conference on Neural Networks, IJCNN 2009 ; Conference date: 14-06-2009 Through 19-06-2009",

}

García, A, Chairez, I, Poznyak, A & Poznyak, T 2009, Robust identification of uncertain nonlinear systems with state constrains by Differential Neural Networks. En 2009 International Joint Conference on Neural Networks, IJCNN 2009., 5178825, Proceedings of the International Joint Conference on Neural Networks, pp. 917-924, 2009 International Joint Conference on Neural Networks, IJCNN 2009, Atlanta, GA, Estados Unidos, 14/06/09. https://doi.org/10.1109/IJCNN.2009.5178825

Robust identification of uncertain nonlinear systems with state constrains by Differential Neural Networks. / García, Alejando; Chairez, Isaac; Poznyak, Alexander et al.
2009 International Joint Conference on Neural Networks, IJCNN 2009. 2009. p. 917-924 5178825 (Proceedings of the International Joint Conference on Neural Networks).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - Robust identification of uncertain nonlinear systems with state constrains by Differential Neural Networks

AU - García, Alejando

AU - Chairez, Isaac

AU - Poznyak, Alexander

AU - Poznyak, Tatyana

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Y1 - 2009

N2 - Non parametric identifier based on Differential Neural Networks is presented. Nonlinear systems with the a priori information about state constrains are considered. Differential Neural Network Identifier includes a projectional operator as part of its structure in order to keep the state restrictions. Stability Analysis based on Lyapunov-Krasovskii energetic-function lets proof the ultimated boundedness of error estimation. Free parameters stability of DNNI (Adaptive Weights) is also proved. Simulation examples regarding to biotechnological process and the Chua's circuit depict the main advantages of the proposed structure against reported Differential Neural Network with similar structure but without projectional operator.

AB - Non parametric identifier based on Differential Neural Networks is presented. Nonlinear systems with the a priori information about state constrains are considered. Differential Neural Network Identifier includes a projectional operator as part of its structure in order to keep the state restrictions. Stability Analysis based on Lyapunov-Krasovskii energetic-function lets proof the ultimated boundedness of error estimation. Free parameters stability of DNNI (Adaptive Weights) is also proved. Simulation examples regarding to biotechnological process and the Chua's circuit depict the main advantages of the proposed structure against reported Differential Neural Network with similar structure but without projectional operator.

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DO - 10.1109/IJCNN.2009.5178825

M3 - Contribución a la conferencia

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SN - 9781424435531

T3 - Proceedings of the International Joint Conference on Neural Networks

SP - 917

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BT - 2009 International Joint Conference on Neural Networks, IJCNN 2009

T2 - 2009 International Joint Conference on Neural Networks, IJCNN 2009

Y2 - 14 June 2009 through 19 June 2009

ER -

Robust identification of uncertain nonlinear systems with state constrains by Differential Neural Networks

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