A Differential Particle Scheme with Successful Parent Selection and its Application to PID Control Tuning

Victor Parque*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Proportional-integral-derivative (PID) control is ubiquitous in industrial automation tasks, and the parameter tuning of the gains is challenging due to nonlinearity and stagnation in local optima. In this paper we present a differential particle scheme based on stagnation-based selection mechanism, and evaluate its effectiveness in the stabilization of a nonlinear inverted pendulum and a magnetic levitation system. Our computational experiments show the feasibility to avoid stagnation, the lower variability of convergence over independent runs, and the feasibility to converge to significantly better fitness values compared to relevant heuristics in the literature. We believe our approach offers the building blocks to build stagnation-free nature inspired optimization algorithms useful for adaptive control and tuning.

Original languageEnglish
Title of host publication2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages522-529
Number of pages8
ISBN (Electronic)9781728183923
DOIs
Publication statusPublished - 2021
Event2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Virtual, Krakow, Poland
Duration: 2021 Jun 282021 Jul 1

Publication series

Name2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings

Conference

Conference2021 IEEE Congress on Evolutionary Computation, CEC 2021
Country/TerritoryPoland
CityVirtual, Krakow
Period21/6/2821/7/1

Keywords

  • Differential evolution
  • Gain tuning
  • Optimization
  • PID control
  • PID tuning
  • Particle swarm optimization
  • Stagnation

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computational Mathematics

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