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Observer Design for Robotic Systems via Takagi–Sugeno Models and Linear Matrix Inequalities

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Handling Uncertainty and Networked Structure in Robot Control

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 42))

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Abstract

This chapter presents a systematic procedure to design observers for mechanical systems. In general, the state space representation of such systems can be naturally expressed as nonlinear descriptor models. The idea is to rewrite the original nonlinear model as a Takagi–Sugeno one and use Lyapunov’s direct method for observer design. This procedure leads to conditions in form of linear matrix inequalities. Two different observer configurations are analysed. The performances of the observers are illustrated on mobile robot.

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Acknowledgments

This work is supported by the Ministry of Higher Education and Research, France, the CNRS, the Nord-Pas-de-Calais Region, and a grant of the Romanian National Authority for Scientific Research, CNCS – UEFISCDI, project number PN-II-RU-TE-2014-4-0942, contract number 88/01.10.2015. The authors gratefully acknowledge the support of these institutions.

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Authors and Affiliations

  1. University of Valenciennes and Hainaut-Cambresis, LAMIH UMR CNRS 8201, Le Mont Houy, 59313, Valenciennes, France

    Víctor Estrada-Manzo & Thierry-Marie Guerra

  2. Department of Automation, Technical University of Cluj-Napoca, Memorandumului 28, 400114, Cluj-Napoca, Romania

    Zsófia Lendek

Authors
  1. Víctor Estrada-Manzo
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  2. Zsófia Lendek
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  3. Thierry-Marie Guerra
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Corresponding author

Correspondence to Víctor Estrada-Manzo .

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Editors and Affiliations

  1. Automation Department, Technical University of Cluj-Napoca, Cluj-Napoca, Romania

    Lucian Busoniu

  2. Automation Department, Technical University of Cluj-Napoca, Cluj-Napoca, Romania

    Levente Tamás

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Estrada-Manzo, V., Lendek, Z., Guerra, TM. (2015). Observer Design for Robotic Systems via Takagi–Sugeno Models and Linear Matrix Inequalities. In: Busoniu, L., Tamás, L. (eds) Handling Uncertainty and Networked Structure in Robot Control. Studies in Systems, Decision and Control, vol 42. Springer, Cham. https://doi.org/10.1007/978-3-319-26327-4_5

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  • DOI: https://doi.org/10.1007/978-3-319-26327-4_5

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  • Print ISBN: 978-3-319-26325-0

  • Online ISBN: 978-3-319-26327-4

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