Optimal control with constrained total variance for Markov jump linear systems with multiplicative noises

Fabio Barbieri and Oswaldo L. V. Costa

International Journal of Systems Science, 2018, vol. 49, issue 6, 1178-1187

Abstract: We consider in this paper the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noises (MJLS-mn for short). Our objective is to present an optimal policy for the problem of maximising the system's total expected output over a finite-time horizon while restricting the weighted sum of its variance to a pre-specified upper-bound value. We obtain explicit conditions for the existence of an optimal control law for this problem as well as an algorithm for obtaining it, extending previous results in the literature. The paper is concluded by applying our results to a portfolio selection problem subject to regime switching.

Date: 2018
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DOI: 10.1080/00207721.2018.1441469

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