Tuning Analog PID Controllers by Multi-Objective Genetic Algorithms with Fuzzy Aggregation

P. H. G. Coelho, J. F. M. Amaral, Y. Bacelar, E. N. Rocha, M. Bentes, T. Souza

2023

Abstract

This paper deals with a procedure for adjusting the gains of a Proportional-Integral-Derivative (PID) controller. Multi-objective genetic algorithms with fuzzy aggregation are used for tuning this controller. To that end, the component values of a known topology of analog PID controller circuit are evolved by a genetic algorithm to yield acceptable performance specifications. A fuzzy aggregator allows multi-objective evaluation for the genetic algorithm. Three objectives regarding the PID reference input signal specifications were considered: overshoot, rise time and settling time. Minimizing these objectives approximates the PID controller output to the reference signal and leads the genetic algorithm to find the best controller gains. A case study is presented to illustrate the procedure.

Paper Citation

in Harvard Style

H. G. Coelho P., M. Amaral J., Bacelar Y., N. Rocha E., Bentes M. and Souza T. (2023). Tuning Analog PID Controllers by Multi-Objective Genetic Algorithms with Fuzzy Aggregation. In Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-648-4, SciTePress, pages 563-571. DOI: 10.5220/0011976900003467

in Bibtex Style

@conference{iceis23,
author={P. H. G. Coelho and J. F. M. Amaral and Y. Bacelar and E. N. Rocha and M. Bentes and T. Souza},
title={Tuning Analog PID Controllers by Multi-Objective Genetic Algorithms with Fuzzy Aggregation},
booktitle={Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2023},
pages={563-571},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011976900003467},
isbn={978-989-758-648-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 25th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Tuning Analog PID Controllers by Multi-Objective Genetic Algorithms with Fuzzy Aggregation
SN - 978-989-758-648-4
AU - H. G. Coelho P.
AU - M. Amaral J.
AU - Bacelar Y.
AU - N. Rocha E.
AU - Bentes M.
AU - Souza T.
PY - 2023
SP - 563
EP - 571
DO - 10.5220/0011976900003467
PB - SciTePress