L1 Optimal Control of Continuous-Time Stochastic Positive Systems
Abstract
We present an L1-optimal control problem class with linear nonnegative costs subject to multiplicative It\^o diffusion processes with elementwise linear input constraints. Forward invariance of the positive orthant is established for the considered stochastic dynamics, and a simulation method consistent with this invariance property is proposed. Both finite-horizon and discounted infinite-horizon stochastic L1-optimal control problems are considered. These problems admit explicit solutions characterized by a vector-valued ordinary differential equation in the finite-horizon case and by an algebraic equation in the infinite-horizon case. Notably, the optimal value function and feedback policy coincide with those of the corresponding deterministic problem, demonstrating robustness to multiplicative stochastic uncertainty. A portfolio example illustrates our results.
Keywords
Cite
@article{arxiv.2607.03952,
title = {L1 Optimal Control of Continuous-Time Stochastic Positive Systems},
author = {Alba Gurpegui and Takashi Tanaka and Anders Rantzer},
journal= {arXiv preprint arXiv:2607.03952},
year = {2026}
}
Comments
14 Pages. 2 Figures. Accepted for publication in IEEE Control Systems Letters (L-CSS) and under review for the 65th IEEE Conference in decision and control 2026 (CDC)