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We study Mean Field stochastic control problems where the cost function and the state dynamics depend upon the joint distribution of the controlled state and the control process. We prove suitable versions of the Pontryagin stochastic…

Optimization and Control · Mathematics 2018-06-26 Beatrice Acciaio , Julio Backhoff-Veraguas , Rene Carmona

An optimal control problem with an infinite horizon quadratic cost functional for a linear system with a known additive disturbance is considered. The feature of this problem is that a weight matrix of the control cost in the cost…

Optimization and Control · Mathematics 2016-03-08 Valery Y. Glizer , Oleg Kelis

The paper deals with an optimal control problem in a dynamical system described by a linear differential equation with the Caputo fractional derivative. The goal of control is to minimize a Bolza-type cost functional, which consists of two…

Optimization and Control · Mathematics 2019-09-25 Mikhail Gomoyunov

The mathematical modeling of numerous real-world applications results in hierarchical optimization problems with two decision makers where at least one of them has to solve an optimal control problem of ordinary or partial differential…

Optimization and Control · Mathematics 2019-06-20 Patrick Mehlitz , Gerd Wachsmuth

This paper discusses the problem of assembly line control and introduces an optimal control formulation that can be used to improve the performance of the assembly line, in terms of cycle time minimization, resources' utilization, etc. A…

Optimization and Control · Mathematics 2020-10-01 Francesco Liberati , Andrea Tortorelli , Cesar Mazquiaran , Muhammad Imran , Martina Panfili

We provide a technique to obtain provably optimal control sequences for quantum systems under the influence of time-correlated multiplicative control noise. Utilizing the circuit-level noise model introduced in [Phys. Rev. Research 3,…

In this paper we develop necessary conditions for optimality, in the form of the stochastic Pontryagin maximum principle, for controlled equations with pointwise delay in the state and with control dependent noise, in the general case of…

Optimization and Control · Mathematics 2018-11-29 Giuseppina Guatteri , Federica Masiero

In this paper, we study a class of fractional optimal control problems. A necessary condition for the existence of an optimal control is provided in the literature. It is commonly given as the existence of a solution of a fractional…

Optimization and Control · Mathematics 2012-03-08 Loïc Bourdin

The purpose of this work is to study an optimal control problem for a semilinear elliptic partial differential equation with a linear combination of Dirac measures as a forcing term; the control variable corresponds to the amplitude of such…

Optimization and Control · Mathematics 2023-07-04 Enrique Otarola

We derive the Pontryagin maximum principle and $Q$-functions for the relaxed control of noisy rough differential equations. Our main tool is the development of a novel differentiation procedure along `spike variation' perturbations of the…

Optimization and Control · Mathematics 2026-01-12 Estepan Ashkarian , Prakash Chakraborty , Harsha Honnappa , Samy Tindel

This paper is concerned with the stochastic recursive optimal control problem with mixed delay. The connection between Pontryagin's maximum principle and Bellman's dynamic programming principle is discussed. Without containing any…

Optimization and Control · Mathematics 2019-12-24 Weijun Meng , Jingtao Shi

Consider a general nonlinear optimal control problem in finite dimension, with constant state and/or control delays. By the Pontryagin Maximum Principle, any optimal trajectory is the projection of a Pontryagin extremal. We establish that,…

Optimization and Control · Mathematics 2018-11-13 Bruno Hérissé , Riccardo Bonalli , Emmanuel Trélat

This paper is concerned with the partial information optimal control problem of wa controlled forward-backward stochastic differential equation of jump diffusion with correlated noises between the system and the observation. For this type…

Probability · Mathematics 2017-08-28 Qingxin Meng

Our work is devoted to the study of Pontryagin's stochastic maximum principle for a mean-field optimal control problem under Peng's $G$-expectation. The dynamics of the controlled state process is given by a stochastic differential equation…

Optimization and Control · Mathematics 2022-11-10 Rainer Buckdahn , Bowen He , Juan Li

The problem of determining the mathematical model of the dynamics of multi-dimensional control systems in the presence of noise under the condition that the correlation functions cannot be found. Known statistical dynamics of linear systems…

General Mathematics · Mathematics 2013-01-29 V. N. Tibabishev

This note is addressed to giving a short introduction to control theory of stochastic systems, governed by stochastic differential equations in both finite and infinite dimensions. We will mainly explain the new phenomenon and difficulties…

Optimization and Control · Mathematics 2016-12-09 Qi Lu , Xu Zhang

We consider a stochastic control problem which is composed of a controlled stochastic differential equation, and whose associated cost functional is defined through a controlled backward stochastic differential equation. Under appropriate…

Probability · Mathematics 2009-02-17 Rainer Buckdahn , Boubakeur Labed , Catherine Rainer , Lazhar Tamer

We prove a stochastic maximum principle ofPontryagin's type for the optimal control of a stochastic partial differential equationdriven by white noise in the case when the set of control actions is convex. Particular attention is paid to…

Probability · Mathematics 2017-06-12 Marco Fuhrman , Ying Hu , Gianmario Tessitore

This article is concerned with an optimal control problem derived by mean-field forward-backward stochastic differential equation with noisy observation, where the drift coefficients of the state equation and the observation equation are…

Optimization and Control · Mathematics 2017-01-09 Guangchen Wang , Hua Xiao , Guojing Xing

Inverse optimal control can be used to characterize behavior in sequential decision-making tasks. Most existing work, however, is limited to fully observable or linear systems, or requires the action signals to be known. Here, we introduce…

Machine Learning · Computer Science 2023-10-31 Dominik Straub , Matthias Schultheis , Heinz Koeppl , Constantin A. Rothkopf
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