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Optimal bounded control with linear stochastic equations and quadratic cost

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Part of the Lecture Notes in Mathematics book series (LNM,volume 31)

Abstract

A method is presented for the computation of optimal control for linear stochastic discrete systems when the control variable is a bounded scalar. The main part of the paper deals with the continuous time problem. The cases with and without penalty on the control variable are studied separately, and expressions for the optimal policy, and the average cost obtained. The best linear policy is investigated, the steady state solution found and the average cost for the best linear policy calculated. Finally the average costs for the best linear policy and the optimal policy are compared.

Keywords

  • Optimal Policy
  • Steady State Solution
  • Riccati Equation
  • Average Cost
  • Random Input

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a summary of a paper which will appear in the Journal of Mathematical Analysis and Applications.

Talk delivered at the international conference, Probabilistic methods in Analysis held at Loutraki Greece between May 22 and 4, 1966

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© 1967 Springer-Verlag

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Kounias, E. (1967). Optimal bounded control with linear stochastic equations and quadratic cost. In: Symposium on Probability Methods in Analysis. Lecture Notes in Mathematics, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0061117

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  • DOI: https://doi.org/10.1007/BFb0061117

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-03902-0

  • Online ISBN: 978-3-540-34970-9

  • eBook Packages: Springer Book Archive