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The paper presents an approach to studying optimal control problems in the space of nonnegative measures with dynamics given by a nonlocal balance law. This approach relies on transforming the balance law into a continuity equation in the…

Optimization and Control · Mathematics 2025-01-30 Nikolay Pogodaev , Maxim Staritsyn

This paper focuses on optimal control problem for a class of discrete-time nonlinear systems. In practical applications, computation time is a crucial consideration when solving nonlinear optimal control problems, especially under real-time…

Optimization and Control · Mathematics 2025-04-01 Chuanzhi Lv , Xunmin Yin , Hongdan Li , Huanshui Zhang

This work focuses on indirect descent methods for optimal control problems governed by nonlinear ordinary differential equations in Banach spaces, viewed as abstract models of distributed dynamics. As a reference line, we revisit the…

Optimization and Control · Mathematics 2025-12-12 Roman Chertovskih , Nikolay Pogodaev , Maxim Staritsyn , A. Pedro Aguiar

We consider nonsmooth optimal control problems subject to a linear elliptic partial differential equation with homogeneous Dirichlet boundary conditions. It is well-known that local solutions satisfy the celebrated Pontryagin maximum…

Optimization and Control · Mathematics 2024-06-28 Daniel Wachsmuth

Motivated by the problem of designing robust composite pulses for Bloch equations in the presence of natural perturbations, we study an abstract optimal ensemble control problem in a probabilistic setting with a general nonlinear…

Optimization and Control · Mathematics 2023-06-26 Roman Chertovskih , Nikolay Pogodaev , Maxim Staritsyn , Antonio Pedro Aguiar

In this paper we introduce a new procedure to solve nonlinear optimal control problems with delays which exploits indirect methods combined with numerical homotopy procedures. It is known that solving this kind of problems via indirect…

Optimization and Control · Mathematics 2017-09-14 Riccardo Bonalli , Bruno Hérissé , Emmanuel Trélat

In this paper, we study the numerical method for stochastic optimal control problems (SOCPs). By reducing the optimal control problem to the discrete case, we derive a discrete stochastic maximum principle (SMP). With the help of this SMP,…

Numerical Analysis · Mathematics 2020-07-14 Mingshang Hu , Lianzi Jiang

Solving real-world optimal control problems are challenging tasks, as the complex, high-dimensional system dynamics are usually unrevealed to the decision maker. It is thus hard to find the optimal control actions numerically. To deal with…

Systems and Control · Electrical Eng. & Systems 2024-01-17 Chengyang Gu , Hui Xiong , Yize Chen

We consider an optimal control problem for a system of local continuity equations on a space of probability measures. Such systems can be viewed as macroscopic models of ensembles of non-interacting particles or homotypic individuals,…

Optimization and Control · Mathematics 2021-10-07 Maxim Staritsyn , Nikolay Pogodaev , Roman Chertovskih , Fernando Lobo Pereira

We present a neural network approach for approximating the value function of high-dimensional stochastic control problems. Our training process simultaneously updates our value function estimate and identifies the part of the state space…

Optimization and Control · Mathematics 2024-05-08 Xingjian Li , Deepanshu Verma , Lars Ruthotto

This paper presents a new method for solving a class of nonlinear optimal control problems with a quadratic performance index. In this method, first the original optimal control problem is transformed into a nonlinear two-point boundary…

Optimization and Control · Mathematics 2014-09-18 Amin Jajarmi , Hamidreza Ramezanpour , Arman Sargolzaei , Pouyan Shafaei

We tackle a nonlinear optimal control problem for a stochastic differential equation in Euclidean space and its state-linear counterpart for the Fokker-Planck-Kolmogorov equation in the space of probabilities. Our approach is founded on a…

Optimization and Control · Mathematics 2024-09-23 Roman Chertovskih , Nikolay Pogodaev , Maxim Staritsyn , A. Pedro Aguiar

We derive first-order Pontryagin optimality conditions for stochastic optimal control with deterministic controls for systems modeled by rough differential equations (RDE) driven by Gaussian rough paths. This Pontryagin Maximum Principle…

Optimization and Control · Mathematics 2025-10-07 Thomas Lew

In this paper, a model of a pair of Dubins vehicles is considered. The vehicles move from an initial position and orientation to final position and orientation. A long the motion, the two vehicles are not allowed to collide however the two…

Robotics · Computer Science 2008-05-01 Heru Tjahjana , Iwan Pranoto , Hari Muhammad , J. Naiborhu , Miswanto

We consider optimal control problems involving nonlinear ordinary differential equations with uncertain inputs. Using the sample average approximation, we obtain optimal control problems with ensembles of deterministic dynamical systems.…

Optimization and Control · Mathematics 2026-02-04 Olena Melnikov , Johannes Milz

In this article we derive a Pontryagin maximum principle (PMP) for discrete-time optimal control problems on matrix Lie groups. The PMP provides first order necessary conditions for optimality; these necessary conditions typically yield two…

Systems and Control · Computer Science 2018-08-07 Karmvir Singh Phogat , Debasish Chatterjee , Ravi Banavar

We introduce a new and efficient numerical method for multicriterion optimal control and single criterion optimal control under integral constraints. The approach is based on extending the state space to include information on a "budget"…

Optimization and Control · Mathematics 2016-01-06 Ajeet Kumar , Alexander Vladimirsky

We consider a state-constrained optimal control problem of a system of two non-local partial-differential equations, which is an extension of the one introduced in a previous work in mathematical oncology. The aim is to minimize the tumor…

Optimization and Control · Mathematics 2018-01-18 Antoine Olivier , Camille Pouchol

Without exact knowledge of the true system dynamics, optimal control of non-linear continuous-time systems requires careful treatment under epistemic uncertainty. In this work, we translate a probabilistic interpretation of the Pontryagin…

Machine Learning · Computer Science 2025-09-03 David Leeftink , Çağatay Yıldız , Steffen Ridderbusch , Max Hinne , Marcel van Gerven

In this paper, we study numerical approximations for optimal control of a class of stochastic partial differential equations with partial observations. The system state evolves in a Hilbert space, whereas observations are given in…

Optimization and Control · Mathematics 2025-04-02 Feng Bao , Yanzhao Cao , Hongjiang Qian
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