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The optimal control of problems that are constrained by partial differential equations with uncertainties and with uncertain controls is addressed. The Lagrangian that defines the problem is postulated in terms of stochastic functions, with…

Optimization and Control · Mathematics 2012-11-19 Eveline Rosseel , Garth N. Wells

We consider the problem of stochastic optimal control in the presence of an unknown disturbance. We characterize the disturbance via empirical characteristic functions, and employ a chance constrained approach. By exploiting properties of…

Optimization and Control · Mathematics 2020-12-16 Vignesh Sivaramakrishnan , Meeko M. K. Oishi

In this paper, we study a stochastic recursive optimal control problem in which the system is governed by a functional forward-backward stochastic differential equation. Under standard assumptions, we establish the dynamic programming…

Probability · Mathematics 2013-01-03 Shaolin Ji , Shuzhen Yang

In this paper we investigate a kind of optimal control problem of coupled forward-backward stochastic system with jumps whose cost functional is defined through a coupled forward-backward stochastic differential equation with Brownian…

Probability · Mathematics 2020-09-15 Qian Lin

This paper focuses on finding approximate solutions to stochastic optimal control problems with control domains being not necessarily convex, where the state trajectory is subject to controlled stochastic differential equations. The…

Optimization and Control · Mathematics 2025-07-15 Shaolin Ji , Rundong Xu

Optimality conditions in the form of a variational inequality are proved for a class of constrained optimal control problems of stochastic differential equations. The cost function and the inequality constraints are functions of the…

Optimization and Control · Mathematics 2018-02-13 Laurent Pfeiffer

The goal of this paper is to solve a class of stochastic optimal control problems numerically, in which the state process is governed by an It\^o type stochastic differential equation with control process entering both in the drift and the…

Optimization and Control · Mathematics 2020-06-05 Richard Archibald , Feng Bao , Jiongmin Yong , Tao Zhou

Stochastic Model Predictive Control addresses uncertainties by incorporating chance constraints that provide probabilistic guarantees of constraint satisfaction. However, simultaneously optimizing over the risk allocation and the feedback…

Systems and Control · Electrical Eng. & Systems 2026-04-07 Filipe Marques Barbosa , Johan Löfberg

This paper is concerned with a finite-horizon inverse control problem, which has the goal of reconstructing, from observations, the possibly non-convex and non-stationary cost driving the actions of an agent. In this context, we present a…

Optimization and Control · Mathematics 2024-06-27 Emiland Garrabe , Hozefa Jesawada , Carmen Del Vecchio , Giovanni Russo

We study the closed-loop solvability of a stochastic linear quadratic optimal control problem for systems governed by stochastic evolution equations. This solvability is established by means of solvability of the corresponding Riccati…

Optimization and Control · Mathematics 2019-01-21 Qi Lü

We present a general approach to prove existence of solutions for optimal control problems not based on typical convexity conditions which quite often are very hard, if not impossible, to check. By taking advantage of several relaxations of…

Optimization and Control · Mathematics 2014-01-21 Pablo Pedregal , Jorge Tiago

In this study, we consider an optimal control problem driven by a stochastic differential system with a stopping time terminal cost functional. We establish the stochastic maximum principle for this new kind of an optimal control problem by…

Optimization and Control · Mathematics 2018-12-11 Shuzhen Yang

This paper considers the relaxed version of the transport problem for general nonlinear control systems, where the objective is to design time-varying feedback laws that transport a given initial probability measure to a target probability…

Systems and Control · Computer Science 2018-07-27 Karthik Elamvazhuthi , Piyush Grover , Spring Berman

In this paper we prove a necessary condition of the optimal control problem for a class of general mean-field forward-backward stochastic systems with jumps in the case where the diffusion coefficients depend on control, the control set…

Optimization and Control · Mathematics 2019-02-20 Tao Hao , Qingxin Meng

We establish the existence of both optimal relaxed controls and strict optimal controls for systems driven by Reflected Stochastic Differential Equations RSDEs. Our approach is based on weak convergence techniques for the associated RSDEs…

Probability · Mathematics 2025-11-25 Ayoub Laayoun , Badr Missaoui

We prove convergence of the proximal policy gradient method for a class of constrained stochastic control problems with control in both the drift and diffusion of the state process. The problem requires either the running or terminal cost…

Optimization and Control · Mathematics 2025-05-27 Ashley Davey , Harry Zheng

This paper investigates the optimal control problem for a class of parabolic equations where the diffusion coefficient is influenced by a control function acting nonlocally. Specifically, we consider the optimization of a cost functional…

Optimization and Control · Mathematics 2025-03-11 Stefana-Lucia Anita , Luca Di Persio

The main contributions of this paper are three fold. First, our primary concern is to investigate a class of stochastic recursive delayed control problems which arise naturally with sound backgrounds but have not been well-studied yet. For…

Optimization and Control · Mathematics 2011-12-06 Li Chen , Jianhui Huang

We solve the optimal control problem of a one-dimensional reflected stochastic differential equation, whose coefficients can be path dependent. The value function of this problem is characterized by a backward stochastic partial…

Probability · Mathematics 2019-01-23 Erhan Bayraktar , Jinniao Qiu

In this paper we consider a constrained parabolic optimal control problem. The cost functional is quadratic and it combines the distance of the trajectory of the system from the desired evolution profile together with the cost of a control.…

Optimization and Control · Mathematics 2021-09-29 Luka Grubišić , Martin Lazar , Ivica Nakić , Martin Tautenhahn