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Solutions to optimal control problems can be discontinuous, even if all the functionals defining the problem are smooth. This can cause difficulties when numerically computing solutions to these problems. While conventional numerical…

Optimization and Control · Mathematics 2022-11-21 Lucian Nita , Eric C. Kerrigan , Eduardo M. G. Vila , Yuanbo Nie

In this paper, the study of nonsmooth optimal control problems (P) involving a controlled sweeping process with three main characteristics is launched. First, the sweeping sets are nonsmooth, time-dependent, and uniformly prox-regular.…

Optimization and Control · Mathematics 2025-12-24 Samara Chamoun , Vera Zeidan

We study the problem of pathwise stochastic optimal control, where the optimization is performed for each fixed realisation of the driving noise, by phrasing the problem in terms of the optimal control of rough differential equations. We…

Probability · Mathematics 2019-06-13 Andrew L. Allan , Samuel N. Cohen

This paper examines stochastic optimal control problems in which the state is perfectly known, but the controller's measure of time is a stochastic process derived from a strictly increasing L\'evy process. We provide dynamic programming…

Optimization and Control · Mathematics 2014-01-03 Andrew Lamperski , Noah J. Cowan

In this paper, we investigate an optimal control problem governed by parabolic equations with measure-valued controls over time. We establish the well-posedness of the optimal control problem and derive the first-order optimality condition…

Optimization and Control · Mathematics 2024-04-04 Wei Gong , Dongdong Liang

We consider a nonlinear control system with vector-valued measures as controls and with dynamics depending on time delayed states. First, we introduce a notion of discontinuous, bounded variation solution associated with this system and…

Optimization and Control · Mathematics 2024-09-02 Giovanni Fusco , Monica Motta , Richard Vinter

We study a family of optimal control problems in which one aims at minimizing a cost that mixes a quadratic control penalization and the variance of the system, both for finitely many agents and for the mean-field dynamics as their number…

Optimization and Control · Mathematics 2021-07-30 Benoît Bonnet , Francesco Rossi

In recent papers it has been suggested that human locomotion may be modeled as an inverse optimal control problem. In this paradigm, the trajectories are assumed to be solutions of an optimal control problem that has to be determined. We…

Optimization and Control · Mathematics 2010-07-26 Yacine Chitour , Frédéric Jean , Paolo Mason

This paper presents a novel convex optimization-based method for finding the globally optimal solutions of a class of mixed-integer non-convex optimal control problems. We consider problems with non-convex constraints that restrict the…

Optimization and Control · Mathematics 2019-11-21 Danylo Malyuta , Behcet Acikmese

In this manuscript, we consider a control system governed by a general ordinary differential equation on a Riemannian manifold, with its endpoints satisfying some inequalities and equalities, and its control constrained to a closed convex…

Optimization and Control · Mathematics 2020-11-06 Li Deng

Optimal control theory is usually formulated as an indirect method requiring the solution of a two-point boundary value problem. Practically, the solution is obtained by iterative forward and backward propagation of quantum wavepackets.…

Quantum Physics · Physics 2020-10-09 Alejandro R. Ramos Ramos , Oliver Kühn

We study the singular stochastic optimal control problem with model uncertainty, where the necessary conditions determined by the corresponding maximum principle are trivial. Robust integral form and pointwise second order necessary…

Optimization and Control · Mathematics 2025-12-09 Guangdong Jing

An optimal control of a steady state thermistor problem is considered, where the convective boundary coefficient is taken as the control variable. A distinctive feature of this paper is that the problem is considered in arbitrary…

Optimization and Control · Mathematics 2019-02-06 Volodymyr Hrynkiv , Sergiy Koshkin

This paper presents a Successive Convexification ($ \texttt{SCvx} $) algorithm to solve a class of non-convex optimal control problems with certain types of state constraints. Sources of non-convexity may include nonlinear dynamics and…

Optimization and Control · Mathematics 2017-10-23 Yuanqi Mao , Daniel Dueri , Michael Szmuk , Behçet Açıkmeşe

We study an explicit mirror-descent method for finite-horizon deterministic optimal control problems. The method is motivated by Pontryagin's maximum principle: at each iteration, one solves the state and adjoint equations and updates the…

Optimization and Control · Mathematics 2026-05-05 Ye Feng , Jianfeng Lu

In this paper, problems of optimal control are considered where in the objective function, in addition to the control cost there is a tracking term that measures the distance to a desired stationary state. The tracking term is given by some…

Optimization and Control · Mathematics 2020-06-15 Martin Gugat , Michael Schuster , Enrique Zuazua

The solutions to surface evolution problems like mean curvature flow can be expressed as value functions of suitable stochastic control problems, obtained as limit of a family of regularised control problems. The control-theoretical…

Analysis of PDEs · Mathematics 2020-05-22 Nicolas Dirr , Federica Dragoni , Raffaele Grande

This paper investigates the optimal harvesting strategy for a single species living in random environments whose growth is given by a regime-switching diffusion. Harvesting acts as a (stochastic) control on the size of the population. The…

Optimization and Control · Mathematics 2016-08-02 Qingshuo Song , Richard Stockbridge , Chao Zhu

We shall consider a stochastic maximum principle of optimal control for a control problem associated with a stochastic partial differential equations of the following type: d x(t) = (A(t) x(t) + a (t, u(t)) x(t) + b(t, u(t)) dt +…

Probability · Mathematics 2012-02-20 AbdulRahman Al-Hussein

Given an infeasible, unbounded, or pathological convex optimization problem, a natural question to ask is: what is the smallest change we can make to the problem's parameters such that the problem becomes solvable? In this paper, we address…

Optimization and Control · Mathematics 2020-01-30 Shane Barratt , Guillermo Angeris , Stephen Boyd