Development of a Methodology for Dynamic Motor Control with Machine Learning

David Aguilar Robles; Ma. del Carmen Santiago Díaz; Ana Claudia Zenteno Vázquez; Yeiny Romero Hernández; Judith  Pérez Marcial; Gustavo T. Rubín Linares

doi:10.61467/2007.1558.2023.v14i3.406

Development of a Methodology for Dynamic Motor Control with Machine Learning

Authors

David Aguilar Robles Benemérita Universidad Autónoma de Puebla
Ma. del Carmen Santiago Díaz Benemérita Universidad Autónoma de Puebla
Ana Claudia Zenteno Vázquez Benemérita Universidad Autónoma de Puebla
Yeiny Romero Hernández Benemérita Universidad Autónoma de Puebla
Judith Pérez Marcial Benemérita Universidad Autónoma de Puebla
Gustavo T. Rubín Linares Benemérita Universidad Autónoma de Puebla

DOI:

https://doi.org/10.61467/2007.1558.2023.v14i3.406

Keywords:

Machine learning, dynamic control, intelligent assistants

Abstract

In robotics, the problem of precision in position control of the different motor systems requires the evaluation of multiple variables in real time in order not to cause instability in the robot due to processing time. In this work, a methodology based on automatic learning of motor systems is proposed in order to be able to generate control actions in advance of their measurement and processing, for which a second-order system and its response to disturbances such as step signals are proposed.

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Published

2023-12-31

How to Cite

Aguilar Robles, D., Santiago Díaz, M. del C., Zenteno Vázquez, A. C., Romero Hernández, Y., Pérez Marcial, J., & Rubín Linares, G. T. (2023). Development of a Methodology for Dynamic Motor Control with Machine Learning. International Journal of Combinatorial Optimization Problems and Informatics, 14(3), 42–52. https://doi.org/10.61467/2007.1558.2023.v14i3.406