TY - JOUR
T1 - An adaptive control study for the DC motor using meta-heuristic algorithms
AU - Rodríguez-Molina, Alejandro
AU - Villarreal-Cervantes, Miguel Gabriel
AU - Aldape-Pérez, Mario
N1 - Publisher Copyright:
© 2017, Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2019/2/13
Y1 - 2019/2/13
N2 - In this work, a comparative study of different meta-heuristic techniques in the adaptive control for the speed regulation of the DC motor with parameters uncertainties is presented. The adaptive control is established as the online solution of a constrained dynamic optimization problem. Several adaptive strategies based on Differential Evolution, Particle Swarm Optimization, Bat Algorithm, Firefly Algorithm, Wolf Search Algorithm and Genetic Algorithm are proposed in order to online tune the parameters of the DC motor control. Simulation results show that proposed adaptive control strategies are a viable alternative to regulate the speed of the motor subject to different operation scenarios. The statistical analysis given in this work shows the features and the differences among strategies, their feasibility to set them up experimentally and also a new hybrid strategy to efficiently solve the problem. In addition, comparative analysis with a robust control approach reveal the advantages of the adaptive strategy based on meta-heuristic techniques in the velocity regulation of the DC motor.
AB - In this work, a comparative study of different meta-heuristic techniques in the adaptive control for the speed regulation of the DC motor with parameters uncertainties is presented. The adaptive control is established as the online solution of a constrained dynamic optimization problem. Several adaptive strategies based on Differential Evolution, Particle Swarm Optimization, Bat Algorithm, Firefly Algorithm, Wolf Search Algorithm and Genetic Algorithm are proposed in order to online tune the parameters of the DC motor control. Simulation results show that proposed adaptive control strategies are a viable alternative to regulate the speed of the motor subject to different operation scenarios. The statistical analysis given in this work shows the features and the differences among strategies, their feasibility to set them up experimentally and also a new hybrid strategy to efficiently solve the problem. In addition, comparative analysis with a robust control approach reveal the advantages of the adaptive strategy based on meta-heuristic techniques in the velocity regulation of the DC motor.
KW - Adaptive control
KW - Heuristic techniques
KW - Optimization problem
KW - Parameter estimation
UR - http://www.scopus.com/inward/record.url?scp=85028770973&partnerID=8YFLogxK
U2 - 10.1007/s00500-017-2797-y
DO - 10.1007/s00500-017-2797-y
M3 - Artículo
SN - 1432-7643
VL - 23
SP - 889
EP - 906
JO - Soft Computing
JF - Soft Computing
IS - 3
ER -