dor_id: 45755

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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/173/170

100.1.#.a: Escobar, F.; Díaz, S.; Gutiérrez, C.; Ledeneva, Y.; Hernández, C.; Rodríguez, D.; Lemus, R.

524.#.#.a: Escobar, F., et al. (2014). Simulation of Control of a Scara Robot Actuated by Pneumatic Artificial Muscles Using RNAPM. Journal of Applied Research and Technology; Vol. 12 Núm. 5. Recuperado de https://repositorio.unam.mx/contenidos/45755

245.1.0.a: Simulation of Control of a Scara Robot Actuated by Pneumatic Artificial Muscles Using RNAPM

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

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

264.#.0.c: 2014

264.#.1.c: 2014-10-01

653.#.#.a: Control Systems; Artificial Neural Networks; Multilayer Perceptron; Pneumatic Artificial Muscle

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: This paper describes the simulation of movement control of a one-degree-of-freedom articulated robot arm SCARAactuated by a pair of McKibben pneumatic artificial muscles. The pneumatic artificial muscle is the actuator andemulates the behavior of biological muscles; due to its nonlinear behavior, there is also a need to develop controlsystems for robot arms using this type of actuator. Research begins with the transfer function that represents, inmathematical language, the movement of the robot arm’s joints; this allows using a PID controller on the transferfunction and generating data to train the Multilayer Perceptron Artificial Neural Network (RNAPM). So far, the PIDcontrol system has been able to control the movement of robot arms but, based on experimental tests, the RNAPMhas proved to outperform the PID control’s response time by up to 2.95 seconds, minimizing the angular error by 1.3°and avoiding the oscillation problem due to its continuous, constant behavior.

773.1.#.t: Journal of Applied Research and Technology; Vol. 12 Núm. 5

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

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

310.#.#.a: Bimestral

264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

doi: https://doi.org/10.1016/S1665-6423(14)70600-5

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

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last_modified: 2024-03-19 14:00:00

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Artículo

Simulation of Control of a Scara Robot Actuated by Pneumatic Artificial Muscles Using RNAPM

Escobar, F.; Díaz, S.; Gutiérrez, C.; Ledeneva, Y.; Hernández, C.; Rodríguez, D.; Lemus, R.

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

Escobar, F., et al. (2014). Simulation of Control of a Scara Robot Actuated by Pneumatic Artificial Muscles Using RNAPM. Journal of Applied Research and Technology; Vol. 12 Núm. 5. Recuperado de https://repositorio.unam.mx/contenidos/45755

Descripción del recurso

Autor(es)
Escobar, F.; Díaz, S.; Gutiérrez, C.; Ledeneva, Y.; Hernández, C.; Rodríguez, D.; Lemus, R.
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
Simulation of Control of a Scara Robot Actuated by Pneumatic Artificial Muscles Using RNAPM
Fecha
2014-10-01
Resumen
This paper describes the simulation of movement control of a one-degree-of-freedom articulated robot arm SCARAactuated by a pair of McKibben pneumatic artificial muscles. The pneumatic artificial muscle is the actuator andemulates the behavior of biological muscles; due to its nonlinear behavior, there is also a need to develop controlsystems for robot arms using this type of actuator. Research begins with the transfer function that represents, inmathematical language, the movement of the robot arm’s joints; this allows using a PID controller on the transferfunction and generating data to train the Multilayer Perceptron Artificial Neural Network (RNAPM). So far, the PIDcontrol system has been able to control the movement of robot arms but, based on experimental tests, the RNAPMhas proved to outperform the PID control’s response time by up to 2.95 seconds, minimizing the angular error by 1.3°and avoiding the oscillation problem due to its continuous, constant behavior.
Tema
Control Systems; Artificial Neural Networks; Multilayer Perceptron; Pneumatic Artificial Muscle
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

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