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We address the output regulation problem for a general class of linear stochastic systems. Specifically, we formulate and solve the ideal full-information and output-feedback problems, obtaining perfect, but non-causal, asymptotic…

Systems and Control · Electrical Eng. & Systems 2021-04-26 Alberto Mellone , Giordano Scarciotti

This paper proposes an approach, Spectral Dynamics Embedding Control (SDEC), to optimal control for nonlinear stochastic systems. This method reveals an infinite-dimensional feature representation induced by the system's nonlinear…

Machine Learning · Computer Science 2025-08-27 Zhaolin Ren , Tongzheng Ren , Haitong Ma , Na Li , Bo Dai

In this paper we study a Pontryagin type stochastic maximum principle for the optimal control of a system, where the state dynamics satisfy a stochastic partial differential equation (SPDE) driven by a two-parameter (time-space) Brownian…

Optimization and Control · Mathematics 2024-01-03 Nacira Agram , Bernt Øksendal , Frank Proske , Olena Tymoshenko

We consider a class of infinite-dimensional singular stochastic control problems. These can be thought of as spatial monotone follower problems and find applications in spatial models of production and climate transition. Let…

Optimization and Control · Mathematics 2026-03-06 Salvatore Federico , Giorgio Ferrari , Frank Riedel , Michael Röckner

This paper focuses on controllability results of stochastic delay partial functional integro-differential equations perturbed by fractional Brownian motion. Sufficient conditions are established using the theory of resolvent operators…

Probability · Mathematics 2015-03-30 El Hassan Lakhel

We study a class of mean-field stochastic differential equations driven by a fractional Brownian motion with Hurst parameter $H\in(1/2,1)$ and a related stochastic control problem. We derive a Pontryagin type maximum principle and the…

Optimization and Control · Mathematics 2017-07-10 Rainer Buckdahn , Shuai Jing

In this paper we deal with global approximation of solutions of stochastic differential equations (SDEs) driven by countably dimensional Wiener process. Under certain regularity conditions imposed on the coefficients, we show lower bounds…

Numerical Analysis · Mathematics 2023-03-24 Łukasz Stępień

Given a submersion $\phi: M \to N$, where $M$ is Riemannian, we construct a stochastic process $X$ on $M$ such that the image $Y:=\phi(X)$ is a (reversed, scaled) mean curvature flow of the fibers of the submersion. The model example is the…

Probability · Mathematics 2022-09-02 Ching-Peng Huang

We consider a mixed stochastic differential equation driven by possibly dependent fractional Brownian motion and Brownian motion. Under mild regularity assumptions on the coefficients, it is proved that the equation has a unique solution.

Probability · Mathematics 2011-11-09 Yuliya Mishura , Georgiy Shevchenko

This work introduces a sequential convex programming framework for non-linear, finite-dimensional stochastic optimal control, where uncertainties are modeled by a multidimensional Wiener process. We prove that any accumulation point of the…

Optimization and Control · Mathematics 2022-09-27 Riccardo Bonalli , Thomas Lew , Marco Pavone

We solve two stochastic control problems in which a player tries to minimize or maximize the exit time from an interval of a Brownian particle, by controlling its drift. The player can change from one drift to another but is subject to a…

Probability · Mathematics 2014-08-19 Robert C. Dalang , Laura Vinckenbosch

In this paper we study general nonlinear stochastic differential equations, where the usual Brownian motion is replaced by a L\'evy process. We also suppose that the coefficient multiplying the increments of this process is merely Lipschitz…

Probability · Mathematics 2007-07-19 Benjamin Jourdain , Sylvie Méléard , Wojbor Woyczynski

In this paper, we study a class of stochastic optimal control problem with jumps under partial information. More precisely, the controlled systems are described by a fully coupled nonlinear multi- dimensional forward-backward stochastic…

Optimization and Control · Mathematics 2009-11-18 Qingxin Meng

We study the convergence of an $N$-particle Markovian controlled system to the solution of a family of stochastic McKean-Vlasov control problems, either with a finite horizon or Schr\"odinger type cost functional. Specifically, under…

Probability · Mathematics 2024-05-22 Francesco C. De Vecchi , Chiara Rigoni

We consider a control problem for the nonlinear stochastic Fokker--Planck equation. This equation describes the evolution of the distribution of nonlocally interacting particles affected by a common source of noise. The system is directed…

Optimization and Control · Mathematics 2025-10-17 Ben Hambly , Philipp Jettkant

In this article we investigate the controllability for neutral stochastic functional integro-differential equations with finite delay, driven by a fractional Brownian motion with Hurst parameter lesser than $1/2$ in a Hilbert space. We…

Probability · Mathematics 2018-09-26 Brahim Boufoussi , Soufiane Mouchtabih

In this paper we provide a complete theoretical analysis of a two-dimensional degenerate non convex singular stochastic control problem. The optimisation is motivated by a storage-consumption model in an electricity market, and features a…

Optimization and Control · Mathematics 2015-10-29 Tiziano De Angelis , Giorgio Ferrari , John Moriarty

We discuss the relevance of geometric concepts in the theory of stochastic differential equations for applications to the theory of non-equilibrium thermodynamics of small systems. In particular, we show how the Eells-Elworthy-Malliavin…

Statistical Mechanics · Physics 2015-06-11 Paolo Muratore-Ginanneschi

This article presents a constrained policy optimization approach for the optimal control of systems under nonstationary uncertainties. We introduce an assumption that we call Markov embeddability that allows us to cast the stochastic…

Optimization and Control · Mathematics 2026-05-11 Sungho Shin , François Pacaud , Emil Contantinescu , Mihai Anitescu

Although statistical inference in stochastic differential equations (SDEs) driven by Wiener process has received significant attention in the literature, inference in those driven by fractional Brownian motion seem to have seen much less…

Statistics Theory · Mathematics 2024-12-10 Trisha Maitra , Sourabh Bhattacharya