AUTOMATIC ADJUSTER FOR NON-STATIONARY OBJECTS WITH EXTENDED AREA OF NORMAL OPERATION

<em>Many objects automatic control unsteady. This is manifested in the change of their parameters. Therefore, periodically adjust the required parameters of the controller. This work is usually carried out rarely. For a long time, regulators are working with is not the optimal settings. The co...

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Main Author: Arthur Pavlov
Format: Article
Language:English
Published: Odessa National Academy of Food Technologies 2017-05-01
Series:Автоматизация технологических и бизнес-процессов
Subjects:
Online Access:http://journals.gsjp.eu/index.php/atbp/article/view/446
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author Arthur Pavlov
author_facet Arthur Pavlov
author_sort Arthur Pavlov
collection DOAJ
description <em>Many objects automatic control unsteady. This is manifested in the change of their parameters. Therefore, periodically adjust the required parameters of the controller. This work is usually carried out rarely. For a long time, regulators are working with is not the optimal settings. The consequence of this is the low quality of many industrial control systems. The solution problem is the use of robust controllers. Explores the possibility of increasing the survivability of automatic control systems by expanding the area of their normal work.  This is achieved by using an artificial neural network simple structure. The method is based on the cooperative effect of neural structures. In this block diagram of the controller is very simple. Such control  effectively compensates the coordinate perturbations if they act  on the control channel.</em>
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spelling doaj.art-da201ed2808f446b9429b8140d8abac32022-12-22T02:49:49ZengOdessa National Academy of Food TechnologiesАвтоматизация технологических и бизнес-процессов2312-31252312-931X2017-05-019110.15673/atbp.v9i1.446331AUTOMATIC ADJUSTER FOR NON-STATIONARY OBJECTS WITH EXTENDED AREA OF NORMAL OPERATIONArthur Pavlov0ONAFT<em>Many objects automatic control unsteady. This is manifested in the change of their parameters. Therefore, periodically adjust the required parameters of the controller. This work is usually carried out rarely. For a long time, regulators are working with is not the optimal settings. The consequence of this is the low quality of many industrial control systems. The solution problem is the use of robust controllers. Explores the possibility of increasing the survivability of automatic control systems by expanding the area of their normal work.  This is achieved by using an artificial neural network simple structure. The method is based on the cooperative effect of neural structures. In this block diagram of the controller is very simple. Such control  effectively compensates the coordinate perturbations if they act  on the control channel.</em>http://journals.gsjp.eu/index.php/atbp/article/view/446Control systemobjectmodelMatLabSimulink.
spellingShingle Arthur Pavlov
AUTOMATIC ADJUSTER FOR NON-STATIONARY OBJECTS WITH EXTENDED AREA OF NORMAL OPERATION
Автоматизация технологических и бизнес-процессов
Control system
object
model
MatLab
Simulink.
title AUTOMATIC ADJUSTER FOR NON-STATIONARY OBJECTS WITH EXTENDED AREA OF NORMAL OPERATION
title_full AUTOMATIC ADJUSTER FOR NON-STATIONARY OBJECTS WITH EXTENDED AREA OF NORMAL OPERATION
title_fullStr AUTOMATIC ADJUSTER FOR NON-STATIONARY OBJECTS WITH EXTENDED AREA OF NORMAL OPERATION
title_full_unstemmed AUTOMATIC ADJUSTER FOR NON-STATIONARY OBJECTS WITH EXTENDED AREA OF NORMAL OPERATION
title_short AUTOMATIC ADJUSTER FOR NON-STATIONARY OBJECTS WITH EXTENDED AREA OF NORMAL OPERATION
title_sort automatic adjuster for non stationary objects with extended area of normal operation
topic Control system
object
model
MatLab
Simulink.
url http://journals.gsjp.eu/index.php/atbp/article/view/446
work_keys_str_mv AT arthurpavlov automaticadjusterfornonstationaryobjectswithextendedareaofnormaloperation