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Fuzzy controllers gains tuning: a constrained nonlinear optimization approach

  • New applications of Artificial Neural Networks in Modeling & Control
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Abstract

This paper presents a methodology for tuning the gains of fuzzy proportional-integral controllers where the concept of closed-loop control system performance is explicitly taken into account. The fuzzy controller gains are found by solving a nonlinear constrained optimization problem considering the system’s dynamics described by a nonlinear model and a set of constraints on the controller gains, control actions and outputs. Experimental results collected on a test-bed show the pertinence of using the proposed tuning technique.

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Acknowledgments

This work has been supported by iCIS-Intelligent Computing in the Internet of Services, Project CENTRO-07-ST24-FEDER-002003.

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Authors and Affiliations

  1. Departamento de Engenharia Electrotécnica, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Campus de Caparica, 2829-516 Caparica, Portugal

    Paulo Gil & Luis Palma

  2. UNINOVA, Institute for the Development of New Tecnologies, Campus de Caparica, 2829-516, Caparica, Portugal

    Catarina Lucena

  3. Department of Informatics Engineering of the University of Coimbra, CISUC, Centre for Informatics and Systems of the University of Coimbra, Polo II, 3030-290, Coimbra, Portugal

    Paulo Gil & Alberto Cardoso

Authors
  1. Paulo Gil
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  2. Catarina Lucena
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  3. Alberto Cardoso
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  4. Luis Palma
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Corresponding author

Correspondence to Paulo Gil.

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Gil, P., Lucena, C., Cardoso, A. et al. Fuzzy controllers gains tuning: a constrained nonlinear optimization approach. Neural Comput & Applic 23, 617–624 (2013). https://doi.org/10.1007/s00521-013-1415-x

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  • DOI: https://doi.org/10.1007/s00521-013-1415-x

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