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We consider a class of stochastic optimal control problems for discrete-time stochastic linear systems which seek for control policies that will steer the probability distribution of the terminal state of the system close to a desired…

Optimization and Control · Mathematics 2020-10-01 Isin M. Balci , Efstathios Bakolas

We consider the problem of controlling an unknown linear dynamical system under a stochastic convex cost and full feedback of both the state and cost function. We present a computationally efficient algorithm that attains an optimal…

Optimization and Control · Mathematics 2022-06-23 Asaf Cassel , Alon Cohen , Tomer Koren

In this paper, we study a stochastic optimal control problem under a type of consistent convex expectation dominated by G-expectation. By the separation theorem for convex sets, we get the representation theorems for this convex expectation…

Optimization and Control · Mathematics 2024-08-21 Xiaojuan Li , Mingshang Hu

In this paper, we focus on a method based on optimal control to address the optimization problem. The objective is to find the optimal solution that minimizes the objective function. We transform the optimization problem into optimal…

Optimization and Control · Mathematics 2023-09-12 Yeming Xu , Ziyuan Guo , Hongxia Wang , Huanshui Zhang

In this paper, we derive sufficient and necessary maximum principles for a stochastic optimal control problem where the system state is given by a controlled stochastic differential equation with default. We prove existence of a unique…

Optimization and Control · Mathematics 2021-05-26 Khalida Bachir Cherif , Nacira Agram , Kristina Dahl

In this paper, we consider optimal control problems derived by stochastic systems with delay, where control domains are non-convex and the diffusion coefficients depend on control variables. By an estimate of the integral of…

Optimization and Control · Mathematics 2022-10-25 Qixia Zhang

This paper investigates optimal control problems for delayed systems governed by Infinitely Anticipated Backward Stochastic Differential Equations (IABSDEs). Unlike existing frameworks limited to bounded delays, we introduce a generalized…

Optimization and Control · Mathematics 2025-12-22 Guanwei Cheng

In this paper, we consider the stochastic optimal control problem for a generalized Volterra control system. The corresponding state process is a kind of a generalized stochastic Volterra integral differential equations. We prove the…

Optimization and Control · Mathematics 2023-12-22 Yuhang Li , Yuecai Han

We investigate constrained optimal control problems for linear stochastic dynamical systems evolving in discrete time. We consider minimization of an expected value cost over a finite horizon. Hard constraints are introduced first, and then…

Optimization and Control · Mathematics 2011-07-07 Eugenio Cinquemani , Mayank Agarwal , Debasish Chatterjee , John Lygeros

We investigate a stochastic optimal control problem where the controlled system is depicted as a stochastic differential delayed equation; however, at the terminal time, the state is constrained in a convex set. We firstly introduce an…

Probability · Mathematics 2017-05-12 Jiaqiang Wen , Yufeng Shi

The maximum principle for optimal control problems of fully coupled forward-backward doubly stochastic differential equations (FBDSDEs in short) in the global form is obtained, under the assumptions that the diffusion coefficients do not…

Optimization and Control · Mathematics 2012-05-28 Liangquan Zhang , Yufeng Shi

This paper introduces a new formulation for stochastic optimal control and stochastic dynamic optimization that ensures safety with respect to state and control constraints. The proposed methodology brings together concepts such as…

Systems and Control · Electrical Eng. & Systems 2021-02-19 Marcus Aloysius Pereira , Ziyi Wang , Ioannis Exarchos , Evangelos A. Theodorou

In this paper, we study a discrete-time stochastic optimal control problem under distribution uncertainty with convex control domain. By weak convergence method and Sion's minimax theorem, we obtain the variational inequality for cost…

Optimization and Control · Mathematics 2022-06-28 Mingshang Hu , Shaolin Ji , Xiaojuan Li

In this paper we are concerned with a new type of backward equations with anticipation which we call neutral backward stochastic functional differential equations. We obtain the existence and uniqueness and prove a comparison theorem. As an…

Optimization and Control · Mathematics 2013-01-15 Wenning Wei

This paper is concerned with a linear quadratic optimal control problem of delayed backward stochastic differential equations. An explicit representation is derived for the optimal control, which is a linear feedback of the entire past…

Optimization and Control · Mathematics 2020-08-07 Weijun Meng , Jingtao Shi

Robust control of complex engineered and biological systems hinges on the integration of feedforward and feedback mechanisms. This is exemplified in neural motor control, where feedforward muscle co-contraction complements sensory-driven…

Optimization and Control · Mathematics 2026-03-06 Bastien Berret , Frédéric Jean

In this paper, we investigate the controlled system described by forward-backward stochastic differential equations with the control contained in drift, diffusion and generator of BSDE. A new verification theorem is derived within the…

Optimization and Control · Mathematics 2012-05-28 Liangquan Zhang

This paper focuses on the discrete-time backward stochastic linear quadratic (BSLQ) optimal control problem with nonhomogeneous system terms and cost function cross terms. The terminal constraint of such systems distinguishes it from…

Optimization and Control · Mathematics 2026-04-14 Hu Ligui , Meng Qingxin , Tang Maoning

This paper investigates a new class of homogeneous stochastic control problems with cone control constraints, extending the classical homogeneous stochastic linear-quadratic (LQ) framework to encompass nonlinear system dynamics and…

Optimization and Control · Mathematics 2025-07-30 Ying Hu , Xiaomin Shi , Zuo Quan Xu

We propose a novel reformulation of the stochastic optimal control problem as an approximate inference problem, demonstrating, that such a interpretation leads to new practical methods for the original problem. In particular we characterise…

Machine Learning · Computer Science 2010-09-22 Konrad Rawlik , Marc Toussaint , Sethu Vijayakumar