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A unified framework for identification and control

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Feedback Control, Nonlinear Systems, and Complexity

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 202))

Abstract

In this paper we examine some of the recent complexity results in worst case deterministic, or control-oriented system identification. We use these as motivation for introducing a unified approach for iterative system identification and control. The approach is an iterative procedure for refining the uncertainty set via robust control based model invalidation and can be viewed as a systematic way of efficiently searching for a controller delivering a certain desired level of performance to the plant. As a result, either the performance goal will be met or the entire uncertainty set will be invalidated in accordance with our modeling and control method biases. We will comment on the computations involved in such a procedure and provide some results for a particular model structure.

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Authors and Affiliations

  1. Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 02139, Cambridge, MA, USA

    Munther A. Dahleh & Mitchell M. Livstone

Authors
  1. Munther A. Dahleh
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  2. Mitchell M. Livstone
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Bruce Allen Francis Allen Robert Tannenbaum

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© 1995 Springer-Verlag London Limited

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Dahleh, M.A., Livstone, M.M. (1995). A unified framework for identification and control. In: Francis, B.A., Tannenbaum, A.R. (eds) Feedback Control, Nonlinear Systems, and Complexity. Lecture Notes in Control and Information Sciences, vol 202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0027670

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  • DOI: https://doi.org/10.1007/BFb0027670

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-19943-4

  • Online ISBN: 978-3-540-39364-1

  • eBook Packages: Springer Book Archive

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