Optimal Control of Noisy Finite-State Markov Processes

Adrian Segall

doi:10.1109/TAC.1977.1101447

Optimal Control of Noisy Finite-State Markov Processes

Adrian Segall

Massachusetts Institute of Technology

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

This paper treats the problem of optimal control of finite-state Markov processes observed in noise. Two types of noisy observations are considered: additive white Gaussian noise and jump-type observations. Sufficient conditions for the optimality of a control law are obtained similar to the stochastic Hamilton-Jacobi equation for perfectly observed Markov processes. An illustrative example concludes the paper.

Original language	English
Pages (from-to)	179-186
Number of pages	8
Journal	IEEE Transactions on Automatic Control
Volume	22
Issue number	2
DOIs	https://doi.org/10.1109/TAC.1977.1101447
State	Published - Apr 1977
Externally published	Yes

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10.1109/TAC.1977.1101447

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Optimal Control of Noisy Finite-State Markov Processes

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