Swarm-Inspired Algorithms to Optimize a Nonlinear Gaussian Adaptive PID Controller

Erickson Diogo Pereira Puchta; Priscilla Bassetto; Lucas Henrique Biuk; Marco Antônio Itaborahy Filho; Attilio Converti; Mauricio dos Santos Kaster; Hugo Valadares Siqueira

LAPSE

Living Archive for Process Systems Engineering

LAPSE:2023.32828

Published Article

LAPSE:2023.32828

Swarm-Inspired Algorithms to Optimize a Nonlinear Gaussian Adaptive PID Controller

Erickson Diogo Pereira Puchta, Priscilla Bassetto, Lucas Henrique Biuk, Marco Antônio Itaborahy Filho, Attilio Converti, Mauricio dos Santos Kaster, Hugo Valadares Siqueira

April 20, 2023

This work deals with metaheuristic optimization algorithms to derive the best parameters for the Gaussian Adaptive PID controller. This controller represents a multimodal problem, where several distinct solutions can achieve similar best performances, and metaheuristics optimization algorithms can behave differently during the optimization process. Finding the correct proportionality between the parameters is an arduous task that often does not have an algebraic solution. The Gaussian functions of each control action have three parameters, resulting in a total of nine parameters to be defined. In this work, we investigate three bio-inspired optimization methods dealing with this problem: Particle Swarm Optimization (PSO), the Artificial Bee Colony (ABC) algorithm, and the Whale Optimization Algorithm (WOA). The computational results considering the Buck converter with a resistive and a nonlinear load as a case study demonstrated that the methods were capable of solving the task. The results are presented and compared, and PSO achieved the best results.

Record ID

LAPSE:2023.32828

Keywords

ABC, GAPID controller, Optimization, PSO, WOA

Subject

Process Control

Suggested Citation

Puchta EDP, Bassetto P, Biuk LH, Itaborahy Filho MA, Converti A, Kaster MDS, Siqueira HV. Swarm-Inspired Algorithms to Optimize a Nonlinear Gaussian Adaptive PID Controller. (2023). LAPSE:2023.32828

Author Affiliations

Puchta EDP: Graduate Program in Production Engineering, Federal University of Technology-Paraná (UTFPR), Dr. Washington Subtil Chueire St. 330, Jardim Carvalho, Ponta Grossa 84017-22, Brazil [ORCID]
Bassetto P: Graduate Program in Production Engineering, Federal University of Technology-Paraná (UTFPR), Dr. Washington Subtil Chueire St. 330, Jardim Carvalho, Ponta Grossa 84017-22, Brazil [ORCID]
Biuk LH: Graduate Program in Electrical Engineering, Federal University of Technology-Paraná (UTFPR), Dr. Washington Subtil Chueire St. 330, Jardim Carvalho, Ponta Grossa 84017-22, Brazil [ORCID]
Itaborahy Filho MA: Graduate Program in Electrical Engineering, Federal University of Technology-Paraná (UTFPR), Dr. Washington Subtil Chueire St. 330, Jardim Carvalho, Ponta Grossa 84017-22, Brazil [ORCID]
Converti A: Department of Civil, Chemical and Environmental Engineering, University of Genoa, Via Balbi 5, 16126 Genoa, Italy [ORCID]
Kaster MDS: Graduate Program in Electrical Engineering, Federal University of Technology-Paraná (UTFPR), Dr. Washington Subtil Chueire St. 330, Jardim Carvalho, Ponta Grossa 84017-22, Brazil [ORCID]
Siqueira HV: Graduate Program in Production Engineering, Federal University of Technology-Paraná (UTFPR), Dr. Washington Subtil Chueire St. 330, Jardim Carvalho, Ponta Grossa 84017-22, Brazil [ORCID]

Journal Name

Energies

Volume

14

Issue

12

First Page

3385

Year

2021

Publication Date

2021-06-08