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Feedback Linearization with a Neural Network Based Compensation Scheme

  • Conference paper
Intelligent Data Engineering and Automated Learning - IDEAL 2012 (IDEAL 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7435))

Abstract

This paper presents a nonlinear controller for uncertain single-input–single-output (SISO) nonlinear systems. The adopted approach is based on the feedback linearization strategy and enhanced by a Radial Basis Function neural network to cope with modeling inaccuracies and external disturbances that can arise. An application of this nonlinear controller to an electro-hydraulic actuated system subject to an unknown dead-zone input is also presented. The obtained numerical results demonstrate the improved control system performance.

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References

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Author information

Authors and Affiliations

  1. Dep. de Engenharia Mecânica, Universidade Federal do Rio Grande do Norte, Campus Universitário Lagoa Nova, CEP 59072-970, Natal, RN, Brasil

    Josiane M. M. Fernandes, Marcelo C. Tanaka, Raimundo C. S. Freire Júnior & Wallace M. Bessa

Authors
  1. Josiane M. M. Fernandes
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  2. Marcelo C. Tanaka
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  3. Raimundo C. S. Freire Júnior
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  4. Wallace M. Bessa
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, The University of Manchester, M13 9PL, Manchester, UK

    Hujun Yin

  2. Department of Electrical Engineering, Federal University of Rio Grande do Norte, Lagoa Nova, 59072-970, Natal, RN, Brazil

    José A. F. Costa

  3. Department of Teleinformatics Engineering, Federal University of Ceará, Campus of Pici, CP 6005, 60455-760, Fortaleza, CE, Brazil

    Guilherme Barreto

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© 2012 Springer-Verlag Berlin Heidelberg

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Fernandes, J.M.M., Tanaka, M.C., Freire Júnior, R.C.S., Bessa, W.M. (2012). Feedback Linearization with a Neural Network Based Compensation Scheme. In: Yin, H., Costa, J.A.F., Barreto, G. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2012. IDEAL 2012. Lecture Notes in Computer Science, vol 7435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32639-4_72

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  • DOI: https://doi.org/10.1007/978-3-642-32639-4_72

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32638-7

  • Online ISBN: 978-3-642-32639-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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