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Fuzzy logic controller parameter optimization using metaheuristic Cuckoo search algorithm for a magnetic levitation system

Author
García-Gutiérrez, G.; Aviles, D. Arcos; Carrera, E.; Guinjoan, F.; Motoasca, E.; Ayala, P.; Ibarra, A.
Type of activity
Journal article
Journal
Applied sciences
Date of publication
2019-06-16
Volume
9
Number
12
First page
1
Last page
15
DOI
10.3390/app9122458
Project funding
DPI2017-85404-P Control avanzado de sistemas multibus cc embarcados en automóviles
Repository
http://hdl.handle.net/2117/165447 Open in new window
URL
https://www.mdpi.com/2076-3417/9/12/2458 Open in new window
Abstract
The main benefits of fuzzy logic control (FLC) allow a qualitative knowledge of the desired system’s behavior to be included as IF-THEN linguistic rules for the control of dynamical systems where either an analytic model is not available or is too complex due, for instance, to the presence of nonlinear terms. The computational structure requires the definition of the FLC parameters namely, membership functions (MF) and a rule base (RB) defining the desired control policy. However, the optimiza...
Citation
García-Gutiérrez, G. [et al.]. Fuzzy logic controller parameter optimization using metaheuristic Cuckoo search algorithm for a magnetic levitation system. "Applied sciences", 16 Juny 2019, vol. 9, núm. 12, p. 1-15.
Keywords
Cuckoo search algorithm, Fuzzy logic controller, Magnetic levitation system, Meta-heuristics
Group of research
EPIC - Energy Processing and Integrated Circuits
PERC-UPC - Power Electronics Research Centre

Participants

  • García Gutiérrez, Gabriel  (author)
  • Arcos Aviles, Diego Gustavo  (author)
  • Carrera, Enrique  (author)
  • Guinjoan Gispert, Francisco  (author)
  • Motoasca, Emilia  (author)
  • Ayala, Paul  (author)
  • Ibarra, Alexander  (author)

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