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For the first time, some hypersingular nonlinear boundary-value problems with a small parameter~$\varepsilon$ at the highest derivative are described. These problems essentially (qualitatively and quantitatively) differ from the usual…

Analysis of PDEs · Mathematics 2018-02-14 Andrei D. Polyanin , Inna K. Shingareva

A classical optimal control problem posed in the whole space R^2 is perturbed by a singular term of magnitude $\epsilon$^{-1} aimed at driving the trajectories to a prescribed network $\Gamma$. We are interested in the link between the…

Analysis of PDEs · Mathematics 2026-05-25 Mohamed Camar-Eddine , Mériadec Chuberre , Mounir Haddou , Olivier Ley

We consider trajectory optimal control problems in which parameter uncertainty limits the applicability of control trajectories computed prior to travel. Hence, efficient trajectory adjustment is needed to ensure successful travel. However,…

Optimization and Control · Mathematics 2025-04-01 Riley Link , Ethan Ebbighausen

In this paper, we consider a stochastic recursive optimal control problem under model uncertainty. In this framework, the cost function is described by solutions of a family of backward stochastic differential equations. With the help of…

Probability · Mathematics 2020-04-16 Mingshang Hu , Falei Wang

We study a control problem where the state equation is a nonlinear partial differential equation of the calculus of variation in a bounded domain, perturbed by noise. We allow the control to act on the boundary and set stochastic boundary…

Probability · Mathematics 2025-11-26 Stefano Bonaccorsi , Adrian Zalinescu

We consider a one dimensional elliptic distributed optimal control problem with pointwise constraints on the derivative of the state. By exploiting the variational inequality satisfied by the derivative of the optimal state, we obtain…

Numerical Analysis · Mathematics 2021-06-18 Susanne C. Brenner , Li-yeng Sung , Winnifried Wollner

Optimal control under uncertainty is a prevailing challenge for many reasons. One of the critical difficulties lies in producing tractable solutions for the underlying stochastic optimization problem. We show how advanced approximate…

Machine Learning · Computer Science 2024-10-28 Joe Watson , Hany Abdulsamad , Rolf Findeisen , Jan Peters

We study problems of optimal boundary control with systems governed by linear hyperbolic partial differential equations. The objective function is quadratic and given by an integral over the finite time interval $(0,\, T)$ that depends on…

Analysis of PDEs · Mathematics 2018-11-08 Martin Gugat , Falk Hante

In this paper, we consider the problem of multi-objective optimal control of a dynamical system with additive and multiplicative noises with given second moments and arbitrary probability distributions. The objectives are given by quadratic…

Optimization and Control · Mathematics 2014-02-17 Ather Gattami

In this paper we study the worst-case complexity of an inexact Augmented Lagrangian method for nonconvex constrained problems. Assuming that the penalty parameters are bounded, we prove a complexity bound of $\mathcal{O}(|\log(\epsilon)|)$…

Optimization and Control · Mathematics 2021-05-25 Geovani N. Grapiglia , Ya-xiang Yuan

In this paper we study the problem of synthesizing optimal control policies for uncertain continuous-time nonlinear systems from syntactically co-safe linear temporal logic (scLTL) formulas. We formulate this problem as a sequence of…

Systems and Control · Electrical Eng. & Systems 2021-04-16 Max Cohen , Calin Belta

An open question contributed by Yu. Orlov to a recently published volume "Unsolved Problems in Mathematical Systems and Control Theory", V.D. Blondel, A. Megretski (eds), Princeton Univ. Press, 2004, concerns regularization of optimal…

Optimization and Control · Mathematics 2008-09-16 Manuel Guerra , Andrey Sarychev

In this paper, we consider a special class of nonlinear optimal control problems, where the control variables are box-constrained and the objective functional is strongly convex corresponding to control variables and separable with respect…

Optimization and Control · Mathematics 2022-01-20 Hailing Wang , Di Wu , Changjun Yu

We consider controllable linear discrete-time systems with bounded perturbations and present two methods to compute robust controlled invariant sets. The first method tolerates an arbitrarily small constraint violation to compute an…

Optimization and Control · Mathematics 2018-01-03 Matthias Rungger , Paulo Tabuada

In this contribution, we introduce an efficient method for solving the optimal control problem for an unconstrained nonlinear switched system with an arbitrary cost function. We assume that the sequence of the switching modes are given but…

Systems and Control · Computer Science 2017-11-08 Farbod Farshidian , Maryam Kamgarpour , Diego Pardo , Jonas Buchli

We propose a method for open-loop stochastic optimal control of LTI systems based on Taylor approximations of quantile functions. This approach enables efficient computation of quantile functions that arise in chance constrained…

Optimization and Control · Mathematics 2022-09-12 Shawn Priore , Christopher Petersen , Meeko Oishi

The present work is motivated by the asymptotic control theory for a system of linear oscillators: the problem is to design a common bounded scalar control for damping all oscillators in asymptotically minimal time. The motion of the system…

Optimization and Control · Mathematics 2015-09-23 Aleksey Fedorov , Alexander Ovseevich

This paper is devoted to studying the null and approximate controllability of two linear coupled parabolic equations posed on a smooth domain of R^N (N>1) with coupling terms of zero and first orders and one control localized in some…

Analysis of PDEs · Mathematics 2020-04-02 Michel Duprez , Pierre Lissy

We develop a unified framework for semilinear elliptic equations with gradient-dependent nonlinearities and singular weights in strictly convex domains. Considering large solutions of \[ -\Delta u + b(x)\,h(|\nabla u|) + a(x)\,u = f(x)…

Analysis of PDEs · Mathematics 2026-03-24 Dragos-Patru Covei

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
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