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In this paper, we establish some important results for the impulsive wave equation. We begin by proving the existence of a solution. Then, we study the impulse approximate controllability where the control function acts on a subdomain…

Optimization and Control · Mathematics 2021-06-08 Walid Zouhair , Akram Ben Aissa

Trajectory optimization is a fundamental stochastic optimal control problem. This paper deals with a trajectory optimization approach for dynamical systems subject to measurement noise that can be fitted into linear time-varying stochastic…

Systems and Control · Electrical Eng. & Systems 2021-08-24 Prakash Mallick , Zhiyong Chen

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

Significant improvements have been achieved in motion control systems with the availability of high speed power switches and microcomputers on the market. Even though motor drivers are able to provide high torque control bandwidth under…

Systems and Control · Electrical Eng. & Systems 2019-07-09 Gorkem Secer

In this paper we introduce and solve a class of optimal stopping problems of recursive type. In particular, the stopping payoff depends directly on the value function of the problem itself. In a multi-dimensional Markovian setting we show…

Optimization and Control · Mathematics 2021-06-23 Katia Colaneri , Tiziano De Angelis

We consider a control problem where the system is driven by a decoupled as well as a coupled forward-backward stochastic differential equation. We prove the existence of an optimal control in the class of relaxed controls, which are…

Optimization and Control · Mathematics 2017-01-31 Fouzia Baghery , Nabil Khelfallah , Brahim Mezerdi , Isabelle Turpin

This paper rigorously connects the problem of optimal control of McKean-Vlasov dynamics with large systems of interacting controlled state processes. Precisely, the empirical distributions of near-optimal control-state pairs for the…

Probability · Mathematics 2016-09-27 Daniel Lacker

Stochastic optimal control problems have a long tradition in applied probability, with the questions addressed being of high relevance in a multitude of fields. Even though theoretical solutions are well understood in many scenarios, their…

Statistics Theory · Mathematics 2024-05-28 Sören Christensen , Claudia Strauch , Lukas Trottner

We introduce a new method, stepwise method for solving optimal con- trol problems. Our first motivation for new approach emanate from limi- tations on continuous time control functions in PMP. Practically in most of the real world models,…

Optimization and Control · Mathematics 2015-06-26 Mehdi Afshar , Farshad Merrikhbayat , Mohammad Reza Razvan

This paper focuses on optimizing probabilities of events of interest defined over general controlled discrete-time Markov processes. It is shown that the optimization over a wide class of $\omega$-regular properties can be reduced to the…

Probability · Mathematics 2014-07-22 Ilya Tkachev , Alexandru Mereacre , Joost-Pieter Katoen , Alessandro Abate

We propose a general framework for studying optimal impulse control problem in the presence of uncertainty on the parameters. Given a prior on the distribution of the unknown parameters, we explain how it should evolve according to the…

Probability · Mathematics 2017-12-06 N. Baradel , B. Bouchard , Ngoc Minh Dang

In this paper, we consider the stochastic optimal control problem for the interacting particle system. We obtain the stochastic maximum principle of the optimal control system by introducing a generalized backward stochastic differential…

Probability · Mathematics 2025-05-14 Andrey A. Dorogovtsev , Yuecai Han , Kateryna Hlyniana , Yuhang Li

This article treats optimal sparse control problems with multiple constraints defined at intermediate points of the time domain. For such problems with intermediate constraints, we first establish a new Pontryagin maximum principle that…

Optimization and Control · Mathematics 2020-12-22 Yogesh Kumar , Sukumar Srikant , Debasish Chatterjee , Masaaki Nagahara

We study the limit behaviour of upper and lower bounds on expected time averages in imprecise Markov chains; a generalised type of Markov chain where the local dynamics, traditionally characterised by transition probabilities, are now…

Probability · Mathematics 2020-03-27 Natan T'Joens , Jasper De Bock

Time estimation is a fundamental task that underpins precision measurement, global navigation systems, financial markets, and the organisation of everyday life. Many biological processes also depend on time estimation by nanoscale clocks,…

This paper deals with the optimal stopping problem under partial observation for piecewise-deterministic Markov processes. We first obtain a recursive formulation of the optimal filter process and derive the dynamic programming equation of…

Probability · Mathematics 2013-05-28 Adrien Brandejsky , Benoîte de Saporta , François Dufour

This paper studies constrained optimal impulse control problems of a deterministic system described by a (semi)flow, where the performance measures are the discounted total costs including both the costs incurred with applying impulses as…

Optimization and Control · Mathematics 2025-04-28 Alexey Piunovskiy , Yi Zhang

Conditions are established under which the optimal control of processes having both absolutely continuous and singular (with respect to time) controls are equivalent to linear programs over a space of measures on the state and control…

Probability · Mathematics 2017-07-31 Thomas G. Kurtz , Richard H. Stockbridge

We analyze the problem of stochastic optimal control of SDEs where the driver includes a self-exciting stochastic process. Due to the non-Markovian nature of the problem, we apply the stochastic maximum principle approach. We derive a…

Optimization and Control · Mathematics 2026-05-13 Heidar Eyjolfsson , Kristina Rognlien Dahl

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