Optimal Tuning of the Speed Control for Brushless DC Motor Based on Chaotic Online Differential Evolution

Alejandro Rodríguez-Molina, Miguel Gabriel Villarreal-Cervantes, Omar Serrano-Pérez, José Solís-Romero, Ramón Silva-Ortigoza

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

The efficiency in the controller performance of a BLDC motor in an uncertain environment highly depends on the adaptability of the controller gains. In this paper, the chaotic adaptive tuning strategy for controller gains (CATSCG) is proposed for the speed regulation of BLDC motors. The CATSCG includes two sequential dynamic optimization stages based on identification and predictive processes, and also the use of a novel chaotic online differential evolution (CODE) for providing controller gains at each predefined time interval. Statistical comparative results with other tuning approaches evidence that the use of the chaotic initialization based on the Lozi map included in CODE for the CATSCG can efficiently handle the disturbances in the closed-loop system of the dynamic environment.

Original languageEnglish
Article number1977
JournalMathematics
Volume10
Issue number12
DOIs
StatePublished - 1 Jun 2022

Keywords

  • adaptive tuning
  • brushless motor
  • chaotic online differential evolution
  • meta-heuristics
  • online optimization

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