Design of a neural control applied to a high-precision robotic arm
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | spa |
Título da fonte: | Sapienza (Curitiba) |
Texto Completo: | https://journals.sapienzaeditorial.com/index.php/SIJIS/article/view/349 |
Resumo: | The main objective of this work is to present a neural control proposal based on a reference tracking model applied to a high-precision robotic arm, where it will begin by explaining and deducing the mathematical model of the robotic arm which will be represented by a space model, where the input variable will be the mechanical torque and the output variable will be the angle and position control of the robot at each instant of time, what is sought through neural control is through the different changes in the variables input and output find and calibrate a control system that guarantees reference tracking, that is, given a desired path or position, we want the robotic arm to accurately follow the desired position or path with pressure. The reference tracking control system is based on artificial intelligence method of machine learning especially in the field of intelligent neural networks. |
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Design of a neural control applied to a high-precision robotic armDiseño de un control neuronal aplicado a un brazo robótico de alta precisiónProjeto de um controle neural aplicado a um braço robótico de alta precisãoDesign, controle neural, braço robóticoDesign, neural control, robotic armDiseño, control neuronal, brazo robótico.The main objective of this work is to present a neural control proposal based on a reference tracking model applied to a high-precision robotic arm, where it will begin by explaining and deducing the mathematical model of the robotic arm which will be represented by a space model, where the input variable will be the mechanical torque and the output variable will be the angle and position control of the robot at each instant of time, what is sought through neural control is through the different changes in the variables input and output find and calibrate a control system that guarantees reference tracking, that is, given a desired path or position, we want the robotic arm to accurately follow the desired position or path with pressure. The reference tracking control system is based on artificial intelligence method of machine learning especially in the field of intelligent neural networks.El objetivo principal de este este trabajo es presentar un propuesta de control neuronal basado en un modelo de seguimiento de referencia aplicado a un brazo robótico de alta precisión , donde se comenzara explicando y deduciendo el modelo matemático del brazo robótico el cual se lo representara mediante un modelo de espacios, donde la variable de entradas será el torque mecánico y la variable de salida será el control el ángulo y la posición de robot en cada instante de tiempo, lo que se busca mediante el control neuronal es mediante los diferentes cambios en las variables de entrada y de salida encontrar y calibrar un sistema de control que garantice el seguimiento de referencia , es decir dada un trayectoria o posición deseada queremos que el brazo robótico siga con exactitud y presión la posición o trayectoria deseada. El sistema de control de seguimiento de referencia está basado en método de inteligencia artificial de machine learning especialmente en el campo de redes neuronales inteligentes.O objetivo principal deste trabalho é apresentar uma proposta de controle neural baseada em um modelo de rastreamento de referência aplicado a um braço robótico de alta precisão, onde começará explicando e deduzindo o modelo matemático do braço robótico que será representado por um espaço modelo, onde a variável de entrada será o torque mecânico e a variável de saída será o controle de ângulo e posição do robô em cada instante de tempo, o que se busca através do controle neural é através das diferentes mudanças nas variáveis de entrada e saída encontrar e calibrar um sistema de controle que garanta o rastreamento de referência, ou seja, dado um caminho ou posição desejada, queremos que o braço robótico siga com precisão a posição ou caminho desejado com pressão. O sistema de controle de rastreamento de referência é baseado no método de inteligência artificial de aprendizado de máquina, especialmente no campo de redes neurais inteligentes.Sapienza Grupo Editorial2022-05-14info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://journals.sapienzaeditorial.com/index.php/SIJIS/article/view/34910.51798/sijis.v3i2.349Sapienza: International Journal of Interdisciplinary Studies; Vol. 3 No. 2 (2022): Multidisciplinary Contributions; 442-452Sapienza: International Journal of Interdisciplinary Studies; Vol. 3 Núm. 2 (2022): Aportes Multidisciplinarios; 442-452Sapienza: International Journal of Interdisciplinary Studies; v. 3 n. 2 (2022): Contribuições Multidisciplinares; 442-4522675-978010.51798/sijis.v3i2reponame:Sapienza (Curitiba)instname:Sapienza Grupo Editorialinstacron:SAPIENZAspahttps://journals.sapienzaeditorial.com/index.php/SIJIS/article/view/349/223Copyright (c) 2022 Leonela Del Roció de la A Salinas, Rolando Edison Carrera Fernández, Mario Fernando Martínez Marcahttps://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessSalinas, Leonela Del Roció de la A Carrera Fernández, Rolando Edison Martínez Marca, Mario Fernando 2022-12-26T21:19:06Zoai:ojs2.journals.sapienzaeditorial.com:article/349Revistahttps://journals.sapienzaeditorial.com/index.php/SIJISPRIhttps://journals.sapienzaeditorial.com/index.php/SIJIS/oaieditor@sapienzaeditorial.com2675-97802675-9780opendoar:2023-01-12T16:42:56.700173Sapienza (Curitiba) - Sapienza Grupo Editorialfalse |
dc.title.none.fl_str_mv |
Design of a neural control applied to a high-precision robotic arm Diseño de un control neuronal aplicado a un brazo robótico de alta precisión Projeto de um controle neural aplicado a um braço robótico de alta precisão |
title |
Design of a neural control applied to a high-precision robotic arm |
spellingShingle |
Design of a neural control applied to a high-precision robotic arm Salinas, Leonela Del Roció de la A Design, controle neural, braço robótico Design, neural control, robotic arm Diseño, control neuronal, brazo robótico. |
title_short |
Design of a neural control applied to a high-precision robotic arm |
title_full |
Design of a neural control applied to a high-precision robotic arm |
title_fullStr |
Design of a neural control applied to a high-precision robotic arm |
title_full_unstemmed |
Design of a neural control applied to a high-precision robotic arm |
title_sort |
Design of a neural control applied to a high-precision robotic arm |
author |
Salinas, Leonela Del Roció de la A |
author_facet |
Salinas, Leonela Del Roció de la A Carrera Fernández, Rolando Edison Martínez Marca, Mario Fernando |
author_role |
author |
author2 |
Carrera Fernández, Rolando Edison Martínez Marca, Mario Fernando |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Salinas, Leonela Del Roció de la A Carrera Fernández, Rolando Edison Martínez Marca, Mario Fernando |
dc.subject.por.fl_str_mv |
Design, controle neural, braço robótico Design, neural control, robotic arm Diseño, control neuronal, brazo robótico. |
topic |
Design, controle neural, braço robótico Design, neural control, robotic arm Diseño, control neuronal, brazo robótico. |
description |
The main objective of this work is to present a neural control proposal based on a reference tracking model applied to a high-precision robotic arm, where it will begin by explaining and deducing the mathematical model of the robotic arm which will be represented by a space model, where the input variable will be the mechanical torque and the output variable will be the angle and position control of the robot at each instant of time, what is sought through neural control is through the different changes in the variables input and output find and calibrate a control system that guarantees reference tracking, that is, given a desired path or position, we want the robotic arm to accurately follow the desired position or path with pressure. The reference tracking control system is based on artificial intelligence method of machine learning especially in the field of intelligent neural networks. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-05-14 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://journals.sapienzaeditorial.com/index.php/SIJIS/article/view/349 10.51798/sijis.v3i2.349 |
url |
https://journals.sapienzaeditorial.com/index.php/SIJIS/article/view/349 |
identifier_str_mv |
10.51798/sijis.v3i2.349 |
dc.language.iso.fl_str_mv |
spa |
language |
spa |
dc.relation.none.fl_str_mv |
https://journals.sapienzaeditorial.com/index.php/SIJIS/article/view/349/223 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-nd/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Sapienza Grupo Editorial |
publisher.none.fl_str_mv |
Sapienza Grupo Editorial |
dc.source.none.fl_str_mv |
Sapienza: International Journal of Interdisciplinary Studies; Vol. 3 No. 2 (2022): Multidisciplinary Contributions; 442-452 Sapienza: International Journal of Interdisciplinary Studies; Vol. 3 Núm. 2 (2022): Aportes Multidisciplinarios; 442-452 Sapienza: International Journal of Interdisciplinary Studies; v. 3 n. 2 (2022): Contribuições Multidisciplinares; 442-452 2675-9780 10.51798/sijis.v3i2 reponame:Sapienza (Curitiba) instname:Sapienza Grupo Editorial instacron:SAPIENZA |
instname_str |
Sapienza Grupo Editorial |
instacron_str |
SAPIENZA |
institution |
SAPIENZA |
reponame_str |
Sapienza (Curitiba) |
collection |
Sapienza (Curitiba) |
repository.name.fl_str_mv |
Sapienza (Curitiba) - Sapienza Grupo Editorial |
repository.mail.fl_str_mv |
editor@sapienzaeditorial.com |
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1797051608311267328 |