dor_id: 45810

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336.#.#.a: Artículo

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351.#.#.b: Journal of Applied Research and Technology

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856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/112/111

100.1.#.a: Lin, Yunhua; Ling, Lina; Chen, Jiantao

524.#.#.a: Lin, Yunhua, et al. (2015). Combined grey prediction fuzzy control law with application to road tunnel ventilation system. Journal of Applied Research and Technology; Vol. 13 Núm. 2. Recuperado de https://repositorio.unam.mx/contenidos/45810

245.1.0.a: Combined grey prediction fuzzy control law with application to road tunnel ventilation system

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2015

264.#.1.c: 2015-04-01

653.#.#.a: Fuzzy control; Tunnel; Compound control; Ventilation system

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx

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041.#.7.h: eng

520.3.#.a: Road tunnel ventilation system is of high non-linearity and uncertainty, and its exact mathematical model is acquired with very difficulty. In order to effectively control road tunnel ventilation system, a combined grey prediction fuzzy control (CGPFC) law is proposed in the paper. The output of this kind of combined controller is formed by combining outputs of the grey prediction fuzzy controller (GPFC) and the traditional fuzzy control law. The grey predictor is realized by discrete GM(1,1) and it is used to predict the system outputs on line in rolling mode. The simulation and experiment for this new fuzzy control law to be applied in road tunnel ventilation system are conducted. The simulation and the practical application show that the effect of this method is better and it also cost less energy compared to the traditional fuzzy control method. All Rights Reserved © 2015 Universidad Nacional Autónoma de México, Centro de Ciencias Aplicadas y Desarrollo Tecnológico. This is an open access item distributed under the Creative Commons CC License BY-NC-ND 4.0.

773.1.#.t: Journal of Applied Research and Technology; Vol. 13 Núm. 2

773.1.#.o: https://jart.icat.unam.mx/index.php/jart

022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423

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doi: https://doi.org/10.1016/j.jart.2015.06.009

harvesting_date: 2023-11-08 13:10:00.0

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Artículo

Combined grey prediction fuzzy control law with application to road tunnel ventilation system

Lin, Yunhua; Ling, Lina; Chen, Jiantao

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Cita

Lin, Yunhua, et al. (2015). Combined grey prediction fuzzy control law with application to road tunnel ventilation system. Journal of Applied Research and Technology; Vol. 13 Núm. 2. Recuperado de https://repositorio.unam.mx/contenidos/45810

Descripción del recurso

Autor(es)
Lin, Yunhua; Ling, Lina; Chen, Jiantao
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
Combined grey prediction fuzzy control law with application to road tunnel ventilation system
Fecha
2015-04-01
Resumen
Road tunnel ventilation system is of high non-linearity and uncertainty, and its exact mathematical model is acquired with very difficulty. In order to effectively control road tunnel ventilation system, a combined grey prediction fuzzy control (CGPFC) law is proposed in the paper. The output of this kind of combined controller is formed by combining outputs of the grey prediction fuzzy controller (GPFC) and the traditional fuzzy control law. The grey predictor is realized by discrete GM(1,1) and it is used to predict the system outputs on line in rolling mode. The simulation and experiment for this new fuzzy control law to be applied in road tunnel ventilation system are conducted. The simulation and the practical application show that the effect of this method is better and it also cost less energy compared to the traditional fuzzy control method. All Rights Reserved © 2015 Universidad Nacional Autónoma de México, Centro de Ciencias Aplicadas y Desarrollo Tecnológico. This is an open access item distributed under the Creative Commons CC License BY-NC-ND 4.0.
Tema
Fuzzy control; Tunnel; Compound control; Ventilation system
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

Enlaces