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Piecewise-Linear Output-Error Methods for Parameter Estimation in Direction-Dependent Processes

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Hybrid Systems: Computation and Control (HSCC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2993))

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Abstract

abstract In direction-dependent processes, the dynamic responses depend on the direction of the system input. The parameter estimation of these processes under noisy conditions can be somewhat problematic in terms of predictor choice and asymptotic behaviour. For parameter estimation, a convenient way to model direction dependence is to use a piecewise-linear model formulation, whose switching depends on the input direction. This paper analyses a prediction-error minimisation method for direction-dependent processes in terms of piecewise-linear dynamics. In particular, the asymptotic convergence properties are investigated and relevant conditions for the utilisation of the estimation method are given. Further, it is demonstrated that a piecewise-linear output-error predictor is preferable in situations where the impact of disturbances is predominant. The main reason for this is that it separates the disturbances from the process model.

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Authors and Affiliations

  1. Department of Signals and Systems, Chalmers University of Technology, SE-412 96, Göteborg, Sweden

    Fredrik Rosenqvist & Anders Karlstöm

Authors
  1. Fredrik Rosenqvist
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  2. Anders Karlstöm
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Editor information

Editors and Affiliations

  1. University of Pennsylvania,  

    Rajeev Alur

  2. School of Engineering and Applied Science, University of Pennsylvania,  

    George J. Pappas

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© 2004 Springer-Verlag Berlin Heidelberg

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Rosenqvist, F., Karlstöm, A. (2004). Piecewise-Linear Output-Error Methods for Parameter Estimation in Direction-Dependent Processes. In: Alur, R., Pappas, G.J. (eds) Hybrid Systems: Computation and Control. HSCC 2004. Lecture Notes in Computer Science, vol 2993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24743-2_33

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  • DOI: https://doi.org/10.1007/978-3-540-24743-2_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21259-1

  • Online ISBN: 978-3-540-24743-2

  • eBook Packages: Springer Book Archive

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