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Harmony Search with Dynamic Adaptation of Parameters for the Optimization of a Benchmark Controller

  • Cinthia Peraza
  • Fevrier ValdezEmail author
  • Oscar Castillo
Chapter
  • 38 Downloads
Part of the Studies in Computational Intelligence book series (SCI, volume 862)

Abstract

A fuzzy harmony search algorithm (FHS) is presented in this paper. This method uses a fuzzy system for dynamic adaptation of the harmony memory accepting (HMR) and pitch adjustment (PArate) parameters along the iterations, and in this way achieving control of the intensification and diversification of the search space. This method was previously applied to various benchmark controller cases however in this case we decided to apply the proposed FHS to benchmark controller problem with different types of noise: band-limited white noise, pulse noise, and uniform random number noise to check the efficiency for the pro-posed method. A comparison is presented to verify the results obtained with the original harmony search algorithm and fuzzy harmony search algorithm.

Keywords

Harmony search Fuzzy logic Dynamic parameter adaptation Fuzzy controller Benchmark problem 

Notes

Acknowledgements

We would like to express our thanks to CONACYT and Tijuana Institute of Technology for the facilities and resources granted for the development of this research.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Cinthia Peraza
    • 1
  • Fevrier Valdez
    • 1
    Email author
  • Oscar Castillo
    • 1
  1. 1.Tijuana Institute of TechnologyTijuanaMexico

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