NEURO-FUZZY CONTROL OF THE LUMBER DRYING PROCESS

Background. The problem of control over the process of lumber drying is considered. The quality of drying is determined by the modes of operation of power plants that provide heat supply to the drying chamber and the parameters of the moisture content of the dried sawn timber. Recently, in many wo...

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Autores principales:	A.I. Diveev, A.V. Poltavskiy, A. Alhatem
Formato:	article
Lenguaje:	EN RU
Publicado:	Penza State University Publishing House 2021
Materias:	optimal control lumber drying neuro-fuzzy control Motor vehicles. Aeronautics. Astronautics TL1-4050
Acceso en línea:	https://doaj.org/article/57b29d538d824d75bdb94c2485c28d27
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id	oai:doaj.org-article:57b29d538d824d75bdb94c2485c28d27
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spelling	oai:doaj.org-article:57b29d538d824d75bdb94c2485c28d272021-12-01T11:58:39ZNEURO-FUZZY CONTROL OF THE LUMBER DRYING PROCESS10.21685/2307-4205-2021-3-122307-4205https://doaj.org/article/57b29d538d824d75bdb94c2485c28d272021-11-01T00:00:00Zhttps://doaj.org/toc/2307-4205Background. The problem of control over the process of lumber drying is considered. The quality of drying is determined by the modes of operation of power plants that provide heat supply to the drying chamber and the parameters of the moisture content of the dried sawn timber. Recently, in many works, the process of drying sawn timber is considered as an optimal control problem, in which the material to be dried must achieve the specified state by its properties in a minimum time. Materials and methods. To determine the modes of high-quality optimal control and effective change of these modes in the process of drying control, it is necessary to have at each moment of time the exact values of the parameters of the model of the controlled object. These values cannot be accurately determined using measuring instruments. Results and conclusions. Thus, the process of optimally managing the drying of lumber involves uncertainties. To eliminate the problem of uncertainties in the work, it is proposed to use the mathematical apparatus of fuzzy sets to describe them, which, in the process of fuzzification of variables, will translate the undefined values of the model parameters into linguistic terms with certain membership functions. To obtain control actions based on the analysis of linguistic variables, it is proposed to use a neuro-fuzzy control system with Tagaki– Sugeno–Kang logical inference based on the ANFIS neural network, which implements optimal control of sawn timber drying based on the rule base set by the developers of the control system.A.I. DiveevA.V. PoltavskiyA. AlhatemPenza State University Publishing Housearticleoptimal controllumber dryingneuro-fuzzy controlMotor vehicles. Aeronautics. AstronauticsTL1-4050ENRUНадежность и качество сложных систем, Iss 3 (2021)
institution	DOAJ
collection	DOAJ
language	EN RU
topic	optimal control lumber drying neuro-fuzzy control Motor vehicles. Aeronautics. Astronautics TL1-4050
spellingShingle	optimal control lumber drying neuro-fuzzy control Motor vehicles. Aeronautics. Astronautics TL1-4050 A.I. Diveev A.V. Poltavskiy A. Alhatem NEURO-FUZZY CONTROL OF THE LUMBER DRYING PROCESS
description	Background. The problem of control over the process of lumber drying is considered. The quality of drying is determined by the modes of operation of power plants that provide heat supply to the drying chamber and the parameters of the moisture content of the dried sawn timber. Recently, in many works, the process of drying sawn timber is considered as an optimal control problem, in which the material to be dried must achieve the specified state by its properties in a minimum time. Materials and methods. To determine the modes of high-quality optimal control and effective change of these modes in the process of drying control, it is necessary to have at each moment of time the exact values of the parameters of the model of the controlled object. These values cannot be accurately determined using measuring instruments. Results and conclusions. Thus, the process of optimally managing the drying of lumber involves uncertainties. To eliminate the problem of uncertainties in the work, it is proposed to use the mathematical apparatus of fuzzy sets to describe them, which, in the process of fuzzification of variables, will translate the undefined values of the model parameters into linguistic terms with certain membership functions. To obtain control actions based on the analysis of linguistic variables, it is proposed to use a neuro-fuzzy control system with Tagaki– Sugeno–Kang logical inference based on the ANFIS neural network, which implements optimal control of sawn timber drying based on the rule base set by the developers of the control system.
format	article
author	A.I. Diveev A.V. Poltavskiy A. Alhatem
author_facet	A.I. Diveev A.V. Poltavskiy A. Alhatem
author_sort	A.I. Diveev
title	NEURO-FUZZY CONTROL OF THE LUMBER DRYING PROCESS
title_short	NEURO-FUZZY CONTROL OF THE LUMBER DRYING PROCESS
title_full	NEURO-FUZZY CONTROL OF THE LUMBER DRYING PROCESS
title_fullStr	NEURO-FUZZY CONTROL OF THE LUMBER DRYING PROCESS
title_full_unstemmed	NEURO-FUZZY CONTROL OF THE LUMBER DRYING PROCESS
title_sort	neuro-fuzzy control of the lumber drying process
publisher	Penza State University Publishing House
publishDate	2021
url	https://doaj.org/article/57b29d538d824d75bdb94c2485c28d27
work_keys_str_mv	AT aidiveev neurofuzzycontrolofthelumberdryingprocess AT avpoltavskiy neurofuzzycontrolofthelumberdryingprocess AT aalhatem neurofuzzycontrolofthelumberdryingprocess
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NEURO-FUZZY CONTROL OF THE LUMBER DRYING PROCESS

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