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On linear-quadratic-Gaussian control of systems with uncertain statistics

  • Stochastic Control
  • Conference paper
  • First Online:
System Modeling and Optimization

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 38))

Abstract

The problem of linear-quadratic Gaussian control of multivariable linear stochastic systems with uncertain second-order statistical properties is considered. Uncertainty is modeled by allowing process and observation noise spectral density matrices to vary arbitrarily within given classes, and a minimax control formulation is applied to the quadratic objective functional. General theorems proving the existence and characterization of saddle-point solutions to this problem are presented, and the relationship of these results to earlier results on minimax state estimation are discussed.

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References

  1. P.J. Huber, Robust Statistical Procedures. SIAM: Philadelphia, 1977.

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Coordinated Science Laboratory, University of Illinois, 1101 W. Springfield Ave., 61801, Urbana, Illinois

    D. P. Looze, H. V. Poor, K. S. Vastola & J. C. Darragh

Authors
  1. D. P. Looze
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  2. H. V. Poor
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  3. K. S. Vastola
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  4. J. C. Darragh
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Editor information

R. F. Drenick F. Kozin

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© 1982 Springer-Verlag

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Looze, D.P., Poor, H.V., Vastola, K.S., Darragh, J.C. (1982). On linear-quadratic-Gaussian control of systems with uncertain statistics. In: Drenick, R.F., Kozin, F. (eds) System Modeling and Optimization. Lecture Notes in Control and Information Sciences, vol 38. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0006163

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  • DOI: https://doi.org/10.1007/BFb0006163

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-11691-2

  • Online ISBN: 978-3-540-39459-4

  • eBook Packages: Springer Book Archive

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