TY - JOUR
T1 - An adaptive control study for a DC motor using meta-heuristic algorithms
AU - Rodríguez-Molina, Alejandro
AU - Villarreal-Cervantes, Miguel Gabriel
AU - Aldape-Pérez, Mario
N1 - Publisher Copyright:
© 2017
PY - 2017/7
Y1 - 2017/7
N2 - In this work, a comparative study of the use of different meta-heuristic techniques in the adaptive control for the speed regulation of the DC motor with parameters uncertainties is presented. Several adaptive controllers based on the optimizers of Differential Evolution (DE), Particle Swarm Optimization (PSO), Bat Algorithm (BAT), Firefly Algorithm (FFA) and Wolf Search Algorithm (WSA) are proposed in order to on-line tune the parameters of the DC motor. These parameters are used in calculating the control signal. Simulations show the efficacy of each control strategy. Given the results, the controller based on PSO is one of the most promising alternatives for this approach.
AB - In this work, a comparative study of the use of different meta-heuristic techniques in the adaptive control for the speed regulation of the DC motor with parameters uncertainties is presented. Several adaptive controllers based on the optimizers of Differential Evolution (DE), Particle Swarm Optimization (PSO), Bat Algorithm (BAT), Firefly Algorithm (FFA) and Wolf Search Algorithm (WSA) are proposed in order to on-line tune the parameters of the DC motor. These parameters are used in calculating the control signal. Simulations show the efficacy of each control strategy. Given the results, the controller based on PSO is one of the most promising alternatives for this approach.
KW - Adaptive control
KW - heuristics
KW - optimization problems
KW - output regulation
KW - parameter estimation
UR - http://www.scopus.com/inward/record.url?scp=85044308206&partnerID=8YFLogxK
U2 - 10.1016/j.ifacol.2017.08.2164
DO - 10.1016/j.ifacol.2017.08.2164
M3 - Artículo
SN - 2405-8963
VL - 50
SP - 13114
EP - 13120
JO - 20th IFAC World Congress
JF - 20th IFAC World Congress
IS - 1
ER -