Keywords
PID control, particle swarm optimization, grey wolf optimization, Arduino
Abstract
Simple and easy to use methods are of great practical demand in the design of Proportional, Integral, and Derivative (PID) controllers. Controller design criteria are to achieve a good set-point tracking and disturbance rejection with minimal actuator variation. Achieving satisfactory trade-offs between these performance criteria is not easily accomplished with classical tuning methods. A particle swarm optimization technique is proposed to design PID controllers. The design method minimizes a compromise cost function based on both the integral absolute error and control signal total variation criteria. The proposed technique is tested on an Arduino-based Temperature Control Laboratory (TCLab) and compared with the Grey Wolf Optimization algorithm. Both TCLab simulation and physical data show that satisfactory trade-offs between the performance and control effort are enabled with the proposed technique.
Original Publication Citation
https://www.mdpi.com/1999-4893/13/12/315/htm
BYU ScholarsArchive Citation
de Moura Oliveira, Paulo; Hedengren, John; and Solteiro Pires, Eduardo, "Swarm-Based Design of Proportional Integral and Derivative Controllers Using a Compromise Cost Function: An Arduino Temperature Laboratory Case Study" (2020). Faculty Publications. 6182.
https://scholarsarchive.byu.edu/facpub/6182
Document Type
Peer-Reviewed Article
Publication Date
2020-11-30
Permanent URL
http://hdl.lib.byu.edu/1877/8911
Publisher
MDPI
Language
English
College
Ira A. Fulton College of Engineering
Department
Chemical Engineering
Copyright Status
Open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright Use Information
https://lib.byu.edu/about/copyright/