Optimal Control with Noisy Time

Andrew Lamperski, Noah J. Cowan

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

This paper examines stochastic optimal control problems in which the state is perfectly known, but the controller's measure of time is a stochastic process derived from a strictly increasing Lévy process. We provide dynamic programming results for continuous-time finite-horizon control and specialize these results to solve a noisy-time variant of the linear quadratic regulator problem and a portfolio optimization problem with random trade activity rates. For the linear quadratic case, the optimal controller is linear and can be computed from a generalization of the classical Riccati differential equation.

Original languageEnglish (US)
Article number7122256
Pages (from-to)319-333
Number of pages15
JournalIEEE Transactions on Automatic Control
Volume61
Issue number2
DOIs
StatePublished - Feb 2016

Keywords

  • Optimal control
  • stochastic optimal control
  • stochastic systems
  • uncertain time

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