RT Journal Article
T1 Metaheuristic Parameter Identification of Motors Using Dynamic Response Relations
A1 Rodríguez-Abreo, Omar
A1 Rodríguez-Reséndiz, Juvenal
A1 Álvarez-Alvarado, José Manuel
A1 García-Cerezo, Alfonso José
K1 Ecuaciones
AB This article presents the use of the equations of the dynamic response to a step input in metaheuristic algorithm for the parametric estimation of a motor model. The model equations are analyzed, and the relations in steady-state and transient-state are used as delimiters in the search. These relations reduce the number of random parameters in algorithm search and reduce the iterations to find an acceptable result. The tests were implemented in two motors of known parameters to estimate the performance of the modifications in the algorithms. Tests were carried out with three algorithms (Gray Wolf Optimizer, Jaya Algorithm, and Cuckoo Search Algorithm) to prove that the benefits can be extended to various metaheuristics. The search parameters were also varied, and tests were developed with different iterations and populations. The results show an improvement for all the algorithms used, achieving the same error as the original method but with 10 to 50% fewer iterations
PB IOAP-MPDI
YR 2022
FD 2022-05-27
LK https://hdl.handle.net/10630/24490
UL https://hdl.handle.net/10630/24490
LA eng
NO Rodríguez-Abreo O, Rodríguez-Reséndiz J, Álvarez-Alvarado JM, García-Cerezo A. Metaheuristic Parameter Identification of Motors Using Dynamic Response Relations. Sensors. 2022; 22(11):4050. https://doi.org/10.3390/s22114050
NO This research received no external funding. Partial funding for open access charge: Universidad de Málaga
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026