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 language | English (US) |
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Article number | 7122256 |
Pages (from-to) | 319-333 |
Number of pages | 15 |
Journal | IEEE Transactions on Automatic Control |
Volume | 61 |
Issue number | 2 |
DOIs | |
State | Published - Feb 2016 |
Bibliographical note
Publisher Copyright:© 2015 IEEE.
Keywords
- Optimal control
- stochastic optimal control
- stochastic systems
- uncertain time