Fractional PID Position Control Tuned by Bio-Heuristics on an ARM Platform

William Montalvo, Jose Iza, Jonathan Vilema

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


Today, modern applications in the field of industrial control have forced many traditional controls to evolve in order to optimize their industrial processes, which is why this study shows the implementation of a fractional order PID control oriented to the speed of a permanent magnet DC motor. It uses bio-heuristic optimization methods for parameter tuning, and its performance will be compared with an entire order PID control tuned by Euler’s MATLAB software. Unlike the traditional PID control, the fractional PID control to be developed has two additional design parameters that allow a better performance of the system. Moreover, by including bio-inspired optimization techniques such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), it is possible to obtain an optimal response of its parameters, compared to classical methods. On the other hand, for the simulation of the control loop, the software MATLAB/SIMULINK and the microcontroller STM32F407 with Advanced Risk Machine (ARM) technology is used, with which the reading and processing of data is obtained. In order to validate the development of the control carried out, the Integral Time Absolute Error (ITAE) is used, which is a performance index that together with the Wilcoxon method allows to compare the controls carried out. At the end of the paper, the results, the robustness of the control and its viability are shown.

Original languageEnglish
Title of host publicationRecent Advances in Electrical Engineering, Electronics and Energy - Proceedings of the CIT 2020
EditorsMiguel Botto Tobar, Henry Cruz, Angela Díaz Cadena
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages12
ISBN (Print)9783030722074
StatePublished - 2021
Event15th Multidisciplinary International Congress on Science and Technology, CIT 2020 - Quito, Ecuador
Duration: 26 Oct 202030 Oct 2020

Publication series

NameLecture Notes in Electrical Engineering
Volume762 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119


Conference15th Multidisciplinary International Congress on Science and Technology, CIT 2020

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.


  • Ant Colony Optimization (ACO)
  • Fractional Order PID (FOPID)
  • Integral Time Absolute Error (ITAE)
  • Particle Swarm Optimization (PSO)


Dive into the research topics of 'Fractional PID Position Control Tuned by Bio-Heuristics on an ARM Platform'. Together they form a unique fingerprint.

Cite this