Soft Computing

, Volume 23, Issue 3, pp 889–906 | Cite as

An adaptive control study for the DC motor using meta-heuristic algorithms

  • Alejandro Rodríguez-Molina
  • Miguel Gabriel Villarreal-CervantesEmail author
  • Mario Aldape-Pérez
Methodologies and Application


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.


Adaptive control Heuristic techniques Optimization problem Parameter estimation 



The authors acknowledge the support of the Secretaría de Investigación y Posgrado (SIP) under the Projects 20170783 and 20161030, and of the Consejo Nacional de Ciencia y Tecnología (CONACyT) under the Project 281728.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Posgraduate DepartmentInstituto Politécnico Nacional, CIDETECMexico CityMexico

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