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International Conference on Hybrid Intelligent Systems

HIS 2018: Hybrid Intelligent Systems pp 428–437Cite as

Fuzzy Algorithms for Fractional PID Control Systems

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 923))

Abstract

This article investigates the use of fuzzy algorithms for fractional PID control systems. The tuning of the fuzzy controllers is based on the prior knowledge of integer or fractional-order control strategy. The suggested fuzzy controllers are fine tuned using a genetic algorithm (GA). The effectiveness and robustness of the proposed methodology is illustrated through its application on the control of a fractional-order plant. The simulation results show the better performance of nonlinear fuzzy algorithms of fractional-order.

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Acknowledgements

This work is supported by FEDER Funds through the “Programa Operacional Factores de Competitividade - COMPETE” program and by National Funds through FCT “Fundação para a Ciência e a Tecnologia” under the project UID/EEA/00760/2013.

Author information

Authors and Affiliations

  1. GECAD - Knowledge Engineering and Decision Support Research Center, Department of Electrical Engineering, ISEP/IPP - School of Engineering, Polytechnic Institute of Porto, Porto, Portugal

    Ramiro S. Barbosa & Isabel S. Jesus

Authors
  1. Ramiro S. Barbosa
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  2. Isabel S. Jesus
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Corresponding author

Correspondence to Ramiro S. Barbosa .

Editor information

Editors and Affiliations

  1. School of Engineering, Instituto Superior de Engenharia (ISEP/IPP), Porto, Portugal

    Ana Maria Madureira

  2. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  3. Machine Intelligence Research Labs, Auburn, WA, USA

    Niketa Gandhi

  4. Department of Production and Systems, University of Minho, Guimarães, Portugal

    Maria Leonilde Varela

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Barbosa, R.S., Jesus, I.S. (2020). Fuzzy Algorithms for Fractional PID Control Systems. In: Madureira, A., Abraham, A., Gandhi, N., Varela, M. (eds) Hybrid Intelligent Systems. HIS 2018. Advances in Intelligent Systems and Computing, vol 923. Springer, Cham. https://doi.org/10.1007/978-3-030-14347-3_42

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