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Consider a stochastic nonlinear system controlled over a possibly noisy communication channel. An important problem is to characterize the largest class of channels for which there exist coding and control policies so that the closed-loop…

Optimization and Control · Mathematics 2021-02-11 Nicolas Garcia , Christoph Kawan , Serdar Yuksel

This paper is concerned with the partial information optimal control problem of mean-field type under partial observation, where the system is given by a controlled mean-field forward-backward stochastic differential equation with…

Optimization and Control · Mathematics 2017-08-21 Qingxin Meng , Qiuhong Shi , Maoning Tang

This paper studies the controllability of networked multi-input-multi-output (MIMO) systems, in which the network topology is weighted and directed, and the nodes are heterogeneous higher-dimensional linear time-invariant (LTI) dynamical…

Optimization and Control · Mathematics 2020-06-23 Linying Xiang , Peiru Wang , Fei Chen , Guanrong Chen

Control of nonlinear large-scale dynamical networks, e.g., collective behavior of agents interacting via a scale-free connection topology, is a central problem in many scientific and engineering fields. For the linear version of this…

Optimization and Control · Mathematics 2016-06-07 Kenji Kashima

We consider a stochastic control problem where the set of strict (classical) controls is not necessarily convex, and the system is governed by a nonlinear backward stochastic differential equation. By introducing a new approach, we…

Optimization and Control · Mathematics 2008-12-20 Seid Bahlali

This paper is concerned with the null controllability for linear backward stochastic parabolic equations with dynamic boundary conditions and convection terms. Using the classical duality argument, the null controllability is obtained via…

Optimization and Control · Mathematics 2025-01-17 Mahmoud Baroun , Said Boulite , Abdellatif Elgrou , Lahcen Maniar

This paper is devoted to the numerical resolution of McKean-Vlasov control problems via the class of mean-field neural networks introduced in our companion paper [25] in order to learn the solution on the Wasserstein space. We propose…

Optimization and Control · Mathematics 2024-03-20 Huyên Pham , Xavier Warin

We introduce the concept of {\it mean-field optimal control} which is the rigorous limit process connecting finite dimensional optimal control problems with ODE constraints modeling multi-agent interactions to an infinite dimensional…

Optimization and Control · Mathematics 2019-02-20 Massimo Fornasier , Francesco Solombrino

In this paper, we study two kinds of singular optimal controls (SOCs for short) problems where the systems governed by forward-backward stochastic differential equations (FBSDEs for short), in which the control has two components: the…

Optimization and Control · Mathematics 2020-12-22 Liangquan Zhang

We study the exact null controllability of a class of non-autonomous conformable fractional semi-linear evolution systems with nonlocal initial conditions in Hilbert spaces. The analysis is carried out within the framework of conformable…

Optimization and Control · Mathematics 2025-04-22 Dev Prakash Jha , Raju K. George

This article presents a novel class of control policies for networked control of Lyapunov-stable linear systems with bounded inputs. The control channel is assumed to have i.i.d. Bernoulli packet dropouts and the system is assumed to be…

Optimization and Control · Mathematics 2017-11-27 Prabhat K. Mishra , Debasish Chatterjee , Daniel E. Quevedo

This paper is concerned with a class of mean-field type coupled forward-backward stochastic differential equations (MF-FBSDEs, for short), in which the coupling appears in integral terms, terminal terms, and initial terms. Inspired by…

Optimization and Control · Mathematics 2022-03-29 Ran Tian , Zhiyong Yu

This article presents a new characterization of controllability and regional controllability of Deterministic Cellular Automata (CA for short). It focuses on analyzing these problems within the framework of control theory, which have been…

Dynamical Systems · Mathematics 2025-01-07 Sara Dridi

Motivated by infinite-dimensional optimal control problems with endpoint state constraints, in this Note, we introduce the notion of finite codimensional exact controllability for evolution equations. It is shown that this new…

Optimization and Control · Mathematics 2016-12-20 Xu Liu , Qi Lu , Xu Zhang

We study the zero-noise limit for autonomous, one-dimensional ordinary differential equations with discontinuous right-hand sides. Although the deterministic equation might have infinitely many solutions, we show, under rather general…

Probability · Mathematics 2022-05-31 Ulrik Skre Fjordholm , Markus Musch , Andrey Pilipenko

In this paper we propose a new methodology for decision-making under uncertainty using recent advancements in the areas of nonlinear stochastic optimal control theory, applied mathematics, and machine learning. Grounded on the fundamental…

Robotics · Computer Science 2021-07-12 Marcus Pereira , Ziyi Wang , Ioannis Exarchos , Evangelos A. Theodorou

We study the optimal control of discrete time mean filed dynamical systems under partial observations. We express the global law of the filtered process as a controlled system with its own dynamics. Following a dynamic programming approach,…

Optimization and Control · Mathematics 2023-03-13 Jeremy Chichportich , Idris Kharroubi

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

In this paper, we first prove that the mean-field stochastic linear quadratic (MFSLQ for short) control problem with random coefficients has a unique optimal control and derive a preliminary stochastic maximum principle to characterize this…

Optimization and Control · Mathematics 2025-05-28 Jie Xiong , Wen Xu

This work addresses the exact characterization of the covariance dynamics related to linear discrete-time systems subject to both additive and parametric stochastic uncertainties that are potentially unbounded. Using this characterization,…

Systems and Control · Electrical Eng. & Systems 2026-01-22 Kaouther Moussa , Mirko Fiacchini
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