Adaptive Control for the Four-Bar Linkage Mechanism Based on Differential Evolution

Alejandro Rodríguez-Molina, Miguel Gabriel Villarreal-Cervantes, Mario Aldape-Pérez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Position tracking in the four-bar linkage mechanism is an important task in several high precision automation processes in the industry. Accuracy may decrease due to uncertainties, but an adaptive control approach can handle them. In this work, an adaptive control strategy for the trajectory tracking of the four-bar linkage mechanism is presented. This strategy includes an adaptive mechanism based on a dynamic optimization process. In this process, a dynamic optimization problem is stated and solved on-line using a meta-heuristic optimizer to find the best set of control parameters which are used in a PID-computed-torque controller. Differential Evolution is chosen as the optimizer and a variant with an optimum tracking mechanism which allows to maintain the diversity of solutions is proposed in order to handle the changing best solution of the dynamic optimization problem. A full statistical analysis is used to prove the effectiveness of the proposed strategy.

Original languageEnglish
Title of host publication2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509060177
DOIs
StatePublished - 28 Sep 2018
Event2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Rio de Janeiro, Brazil
Duration: 8 Jul 201813 Jul 2018

Publication series

Name2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings

Conference

Conference2018 IEEE Congress on Evolutionary Computation, CEC 2018
Country/TerritoryBrazil
CityRio de Janeiro
Period8/07/1813/07/18

Keywords

  • Adaptive control
  • Differential Evolution
  • Four-Bar Linkage Mechanism

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