Intelligent Search of Values for a Controller Using the Artificial Bee Colony Algorithm to Control the Velocity of Displacement of a Robot
José M. Villegas,
Camilo Caraveo,
David A. Mejía,
José L. Rodríguez,
Yuridia Vega,
Leticia Cervantes,
Alejandro Medina-Santiago
Affiliations
José M. Villegas
Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Blvd. Universitario #1000, Unidad Valle de las Palmas, Tijuana 21500, Mexico
Camilo Caraveo
Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Blvd. Universitario #1000, Unidad Valle de las Palmas, Tijuana 21500, Mexico
David A. Mejía
Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Blvd. Universitario #1000, Unidad Valle de las Palmas, Tijuana 21500, Mexico
José L. Rodríguez
Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Blvd. Universitario #1000, Unidad Valle de las Palmas, Tijuana 21500, Mexico
Yuridia Vega
Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Blvd. Universitario #1000, Unidad Valle de las Palmas, Tijuana 21500, Mexico
Leticia Cervantes
Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Blvd. Universitario #1000, Unidad Valle de las Palmas, Tijuana 21500, Mexico
Alejandro Medina-Santiago
National Institute for Astrophysics, Optics and Electronics, Puebla 72840, Mexico
The optimization is essential in the engineering area and, in conjunction with use of meta-heuristics, has had a great impact in recent years; this is because of its great precision in search of optimal parameters for the solution of problems. In this work, the use of the Artificial Bee Colony Algorithm (ABC) is presented to optimize the values for the variables of a proportional integral controller (PI) to observe the behavior of the controller with the optimized Ti and Kp values. It is proposed using a robot built using the MINDSTORMS version EV3 kit. The objective of this work is to demonstrate the improvement and efficiency of the controllers in conjunction with optimization meta-heuristics. In the results section, we observe that the results improve considerably compared to traditional methods. In this work, the main contribution is the implementation of an optimization algorithm (ABC) applied to a controller (PI), and the results are tested to control the movement of a robot. There are many papers where the kit is used in various domains such as education as well as research for science and technology tasks and some real-world problems by engineering scholars, showing the acceptable result.