CONTROLO 2016 pp 239-249 | Cite as

Grey Wolf, Gravitational Search and Particle Swarm Optimizers: A Comparison for PID Controller Design

  • Paulo Moura OliveiraEmail author
  • Damir Vrančić
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 402)


Nature and biologically inspired metaheuristics can be powerful tools to design PID controllers. The grey wolf optimization is one of these promising and interesting metaheuristics, recently introduced. In this study the grey wolf optimization algorithm is proposed to design PID controllers, and the results obtained compared with the ones obtained with gravitational search and particle swarm optimization algorithms. Simulation results obtained with these three bio-inspired metaheuristics applied to a set of benchmark linear plants are presented, considering the design objective of set-point tracking. The results are also compared with two non-iterative PID tuning techniques.


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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.INESC TEC—INESC Technology and Science Department of Engineering, School of Sciences and TechnologyUniversidade de Trás-os-Montes e Alto Douro, UTADVila RealPortugal
  2. 2.Department of Systems and ControlJožef Stefan InstituteLjubljanaSlovenia

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