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We consider an optimal stochastic impulse control problem over an infinite time horizon motivated by a model of irreversible investment choices with fixed adjustment costs. By employing techniques of viscosity solutions and relying on…

Optimization and Control · Mathematics 2019-02-05 Salvatore Federico , Mauro Rosestolato , Elisa Tacconi

In this paper, we solve an open problem and obtain a general maximum principle for a stochastic optimal control problem where the control domain is an arbitrary non-empty set and all the coefficients (especially the diffusion term and the…

Optimization and Control · Mathematics 2023-02-08 Weijun Meng , Jingtao Shi , Tianxiao Wang , Ji-Feng Zhang

The design of the performance index, also referred to as cost or reward shaping, is central to both optimal control and reinforcement learning, as it directly determines the behaviors, trade-offs, and objectives that the resulting control…

Systems and Control · Electrical Eng. & Systems 2025-10-14 Ayush Rai , Shaoshuai Mou , Brian D. O. Anderson

Physical systems driven away from equilibrium by an external controller dissipate heat to the environment; the excess entropy production in the thermal reservoir can be interpreted as a "cost" to transform the system in a finite time. The…

Statistical Mechanics · Physics 2024-12-31 Jérémie Klinger , Grant M. Rotskoff

We consider cost minimising control problems, in which the dynamical system is constrained by higher order differential equations of Euler-Lagrange type. Following ideas from a previous paper by the first and the third author, we prove that…

Optimization and Control · Mathematics 2021-01-27 Franco Cardin , Cristina Giannotti , Andrea Spiro

This paper considers linear discrete-time systems with additive disturbances, and designs a Model Predictive Control (MPC) law to minimise a quadratic cost function subject to a chance constraint. The chance constraint is defined as a…

Systems and Control · Computer Science 2020-07-15 Shuhao Yan , Paul Goulart , Mark Cannon

This paper consists of a detailed and novel stochastic optimal control analysis of a coupled non-linear dynamical system. The state equations are modeled as additional food provided prey-predator system with Holling Type-III functional…

Optimization and Control · Mathematics 2023-09-01 D. Bhanu Prakash , D. K. K. Vamsi

This paper considers a distributed stochastic optimization problem where the goal is to minimize the time average of a cost function subject to a set of constraints on the time averages of a related stochastic processes called penalties. We…

Information Theory · Computer Science 2016-10-06 B. N. Bharath , Vaishali P

We consider the problem of finding the best memoryless stochastic policy for an infinite-horizon partially observable Markov decision process (POMDP) with finite state and action spaces with respect to either the discounted or mean reward…

Optimization and Control · Mathematics 2022-05-02 Johannes Müller , Guido Montúfar

A general maximum principle (necessary and sufficient conditions) for an optimal control problem governed by a stochastic differential equation driven by an infinite dimensional martingale is established. The solution of this equation takes…

Probability · Mathematics 2012-03-21 AbdulRahman Al-Hussein

Necessary optimality conditions in the form of the maximum principle for control problems with infinite time horizon are considered. Both finite and infinite values of objective functional are allowed since the concept of overtaking or…

Optimization and Control · Mathematics 2017-01-16 Anton O. Belyakov

We consider the problem of learning control policies that optimize a reward function while satisfying constraints due to considerations of safety, fairness, or other costs. We propose a new algorithm, Projection-Based Constrained Policy…

Machine Learning · Computer Science 2020-10-08 Tsung-Yen Yang , Justinian Rosca , Karthik Narasimhan , Peter J. Ramadge

This paper presents a new fast and robust algorithm that provides fuel-optimal impulsive control input sequences that drive a linear time-variant system to a desired state at a specified time. This algorithm is applicable to a broad class…

Optimization and Control · Mathematics 2020-10-06 Adam W. Koenig , Simone D'Amico

In this paper we consider the problem of the optimal control of an ensemble of affine-control systems. After proving the well-posedness of the minimization problem under examination, we establish a $\Gamma$-convergence result that allows us…

Optimization and Control · Mathematics 2023-11-20 Alessandro Scagliotti

Stability of economic model predictive control can be proven under the assumption that a strict dissipativity condition holds. This assumption has a clear interpretation in terms of the so-called rotated stage cost, which must have its…

Optimization and Control · Mathematics 2026-03-10 Mario Zanon

Computational level explanations based on optimal feedback control with signal-dependent noise have been able to account for a vast array of phenomena in human sensorimotor behavior. However, commonly a cost function needs to be assumed for…

Machine Learning · Computer Science 2021-10-22 Matthias Schultheis , Dominik Straub , Constantin A. Rothkopf

In this paper we consider a broad class of infinite horizon discrete-time optimal control models that involve a nonnegative cost function and an affine mapping in their dynamic programming equation. They include as special cases classical…

Optimization and Control · Mathematics 2017-11-29 Dimitri Bertsekas

In this paper, we study a stochastic optimal control problem under a type of consistent convex expectation dominated by G-expectation. By the separation theorem for convex sets, we get the representation theorems for this convex expectation…

Optimization and Control · Mathematics 2024-08-21 Xiaojuan Li , Mingshang Hu

In this paper, error estimates are presented for a certain class of optimal control problems with elliptic PDE-constraints. It is assumed that in the cost functional the state is measured in terms of the energy norm generated by the state…

Numerical Analysis · Mathematics 2014-10-31 Olli Mali

In this paper, we consider the finite-state approximation of a discrete-time constrained Markov decision process (MDP) under the discounted and average cost criteria. Using the linear programming formulation of the constrained discounted…

Optimization and Control · Mathematics 2018-07-10 Naci Saldi
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