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

William Montalvo; Jose Iza; Jonathan Vilema

doi:10.1007/978-3-030-72208-1_16

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

William Montalvo, Jose Iza, Jonathan Vilema

Research Group in Electronics Control and Automation (GIECA)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

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 language	English
Title of host publication	Recent Advances in Electrical Engineering, Electronics and Energy - Proceedings of the CIT 2020
Editors	Miguel Botto Tobar, Henry Cruz, Angela Díaz Cadena
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	211-222
Number of pages	12
ISBN (Print)	9783030722074
DOIs	https://doi.org/10.1007/978-3-030-72208-1_16
State	Published - 2021
Event	15th Multidisciplinary International Congress on Science and Technology, CIT 2020 - Quito, Ecuador Duration: 26 Oct 2020 → 30 Oct 2020

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	762 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	15th Multidisciplinary International Congress on Science and Technology, CIT 2020
Country/Territory	Ecuador
City	Quito
Period	26/10/20 → 30/10/20

Bibliographical note

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

Keywords

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

Access to Document

10.1007/978-3-030-72208-1_16

Cite this

Montalvo, W., Iza, J., & Vilema, J. (2021). Fractional PID Position Control Tuned by Bio-Heuristics on an ARM Platform. In M. Botto Tobar, H. Cruz, & A. Díaz Cadena (Eds.), Recent Advances in Electrical Engineering, Electronics and Energy - Proceedings of the CIT 2020 (pp. 211-222). (Lecture Notes in Electrical Engineering; Vol. 762 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-72208-1_16

Montalvo, William ; Iza, Jose ; Vilema, Jonathan. / Fractional PID Position Control Tuned by Bio-Heuristics on an ARM Platform. Recent Advances in Electrical Engineering, Electronics and Energy - Proceedings of the CIT 2020. editor / Miguel Botto Tobar ; Henry Cruz ; Angela Díaz Cadena. Springer Science and Business Media Deutschland GmbH, 2021. pp. 211-222 (Lecture Notes in Electrical Engineering).

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title = "Fractional PID Position Control Tuned by Bio-Heuristics on an ARM Platform",

abstract = "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{\textquoteright}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.",

keywords = "Ant Colony Optimization (ACO), Fractional Order PID (FOPID), Integral Time Absolute Error (ITAE), Particle Swarm Optimization (PSO)",

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Montalvo, W, Iza, J & Vilema, J 2021, Fractional PID Position Control Tuned by Bio-Heuristics on an ARM Platform. in M Botto Tobar, H Cruz & A Díaz Cadena (eds), Recent Advances in Electrical Engineering, Electronics and Energy - Proceedings of the CIT 2020. Lecture Notes in Electrical Engineering, vol. 762 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 211-222, 15th Multidisciplinary International Congress on Science and Technology, CIT 2020, Quito, Ecuador, 26/10/20. https://doi.org/10.1007/978-3-030-72208-1_16

Fractional PID Position Control Tuned by Bio-Heuristics on an ARM Platform. / Montalvo, William; Iza, Jose; Vilema, Jonathan.
Recent Advances in Electrical Engineering, Electronics and Energy - Proceedings of the CIT 2020. ed. / Miguel Botto Tobar; Henry Cruz; Angela Díaz Cadena. Springer Science and Business Media Deutschland GmbH, 2021. p. 211-222 (Lecture Notes in Electrical Engineering; Vol. 762 LNEE).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Montalvo, William

AU - Iza, Jose

AU - Vilema, Jonathan

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

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Montalvo W, Iza J, Vilema J. Fractional PID Position Control Tuned by Bio-Heuristics on an ARM Platform. In Botto Tobar M, Cruz H, Díaz Cadena A, editors, Recent Advances in Electrical Engineering, Electronics and Energy - Proceedings of the CIT 2020. Springer Science and Business Media Deutschland GmbH. 2021. p. 211-222. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-3-030-72208-1_16

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

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Keywords

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