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Application of Minimum Distortion Filtering to Identification of Linear Systems Having Non-uniform Sampling Period

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System Identification, Environmental Modelling, and Control System Design

Abstract

We consider the problem of identification of continuous time systems when the data is collected using non-uniform sampling periods. We formulate this problem in the context of Nonlinear Filtering. We show how a new class of nonlinear filtering algorithm (Minimum Distortion Filtering) can be applied to this problem. A simple example is used to illustrate the performance of the algorithm. We also compare the results with those obtained from (a particular realization) of Particle Filtering.

The chapter is inspired by the work of Peter Young who has made a life time of contributions to parameter estimation for real world systems.

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Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, University of Newcastle, University Drive, NSW, 2308, Australia

    Graham C. Goodwin & Mauricio G. Cea

Authors
  1. Graham C. Goodwin
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  2. Mauricio G. Cea
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Correspondence to Graham C. Goodwin .

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Editors and Affiliations

  1. Computer Engineering, RMIT University, Swanston Street 10, Melbourne, 3000, Victoria, Australia

    Liuping Wang

  2. Centre de Recherche en, Automatique de Nancy, Université Nancy I, Vandoeuvre-les-Nancy CX, France

    Hugues Garnier

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Goodwin, G.C., Cea, M.G. (2012). Application of Minimum Distortion Filtering to Identification of Linear Systems Having Non-uniform Sampling Period. In: Wang, L., Garnier, H. (eds) System Identification, Environmental Modelling, and Control System Design. Springer, London. https://doi.org/10.1007/978-0-85729-974-1_5

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  • DOI: https://doi.org/10.1007/978-0-85729-974-1_5

  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-973-4

  • Online ISBN: 978-0-85729-974-1

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