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This paper is concerned with a stochastic linear-quadratic optimal control problem in a finite time horizon, where the coefficients of the control system are allowed to be random, and the weighting matrices in the cost functional are…

Optimization and Control · Mathematics 2019-11-12 Jingrui Sun , Jie Xiong , Jiongmin Yong

We consider a class of monotone systems in which the control signal multiplies the state. Among other applications, such bilinear systems can be used to model the evolutionary dynamics of HIV in the presence of combination drug therapy. For…

Optimization and Control · Mathematics 2016-12-01 Neil K. Dhingra , Marcello Colombino , Mihailo R. Jovanović , Anders Rantzer , Roy S. Smith

A Learning Model Predictive Controller (LMPC) for linear system in presented. The proposed controller is an extension of the LMPC [1] and it aims to decrease the computational burden. The control scheme is reference-free and is able to…

Optimization and Control · Mathematics 2019-10-31 Ugo Rosolia , Francesco Borrelli

We take a divide and conquer approach to design controllers for reachability problems given large-scale linear systems with polyhedral constraints on states, controls, and disturbances. Such systems are made of small subsystems with coupled…

Systems and Control · Electrical Eng. & Systems 2022-08-04 Kasra Ghasemi , Sadra Sadraddini , Calin Belta

The Euclidean space notion of convex sets (and functions) generalizes to Riemannian manifolds in a natural sense and is called geodesic convexity. Extensively studied computational problems such as convex optimization and sampling in convex…

Optimization and Control · Mathematics 2020-02-10 Navin Goyal , Abhishek Shetty

The frequency-domain data of a multivariable system in different operating points is used to design a robust controller with respect to the measurement noise and multimodel uncertainty. The controller is fully parametrized in terms of…

Optimization and Control · Mathematics 2017-08-10 Alireza Karimi , Christoph Kammer

We obtain a general concept of triplet of Hilbert spaces with closed (unbounded) embeddings instead of continuous (bounded) ones. The construction starts with a positive selfadjoint operator $H$, that is called the Hamiltonian of the…

Functional Analysis · Mathematics 2025-11-04 Petru Cojuhari , Aurelian Gheondea

Analysis of high-dimensional data is currently a popular field of research, thanks to many applications e.g. in genetics (DNA data in genomewide association studies), spectrometry or web analysis. At the same time, the type of problems that…

Methodology · Statistics 2018-05-25 Jozef Jakubik

We develop a Hilbert space framework for a number of general multi-scale problems from dynamics. The aim is to identify a spectral theory for a class of systems based on iterations of a non-invertible endomorphism. We are motivated by the…

Dynamical Systems · Mathematics 2007-05-23 Dorin Ervin Dutkay , Palle E. T. Jorgensen

In this paper, we design a new iterative algorithm for solving pseudomonotone equilibrium problems in real Hilbert spaces. The advantage of our algorithm is that it requires only one strongly convex programming problem at each iteration.…

Optimization and Control · Mathematics 2018-04-06 Nguyen The Vinh

This article treats three problems of sparse and optimal multiplexing a finite ensemble of linear control systems. Given an ensemble of linear control systems, multiplexing of the controllers consists of an algorithm that selects, at each…

Optimization and Control · Mathematics 2019-05-27 Yogesh Kumar , Sukumar Srikant , Debasish Chatterjee

In this paper, we consider an infinite horizon Linear-Quadratic-Gaussian control problem with controlled and costly measurements. A control strategy and a measurement strategy are co-designed to optimize the trade-off among control…

Systems and Control · Electrical Eng. & Systems 2021-01-01 Yunhan Huang , Quanyan Zhu

We consider a class of infinite-dimensional singular stochastic control problems. These can be thought of as spatial monotone follower problems and find applications in spatial models of production and climate transition. Let…

Optimization and Control · Mathematics 2026-03-06 Salvatore Federico , Giorgio Ferrari , Frank Riedel , Michael Röckner

We propose and discuss a new computational method for the numerical approximation of reachable sets for nonlinear control systems. It is based on the support vector machine algorithm and represents the set approximation as a sublevel set of…

Optimization and Control · Mathematics 2014-12-11 Martin Rasmussen , Janosch Rieger , Kevin Webster

Demixing is the problem of identifying multiple structured signals from a superimposed, undersampled, and noisy observation. This work analyzes a general framework, based on convex optimization, for solving demixing problems. When the…

Information Theory · Computer Science 2013-10-01 Michael B. McCoy , Joel A. Tropp

In this article we consider a consistent convex feasibility problem in a real Hilbert space defined by a finite family of sets $C_i$. We are interested, in particular, in the case where for each $i$, $C_i=Fix (U_i)=\{z\in \mathcal H\mid…

Optimization and Control · Mathematics 2017-03-29 Victor I. Kolobov , Simeon Reich , Rafał Zalas

Quantum ensemble systems arise in a variety of applications, including NMR spectroscopy and robust quantum control. While their theoretical properties have been extensively studied, relatively little attention has been given to the explicit…

Optimization and Control · Mathematics 2025-06-25 Ruikang Liang , Gong Cheng

This note proposes a general control approach, called vector-field guided constraint-following control, to solve the dynamics control problem of geometric path-following for a class of uncertain mechanical systems. More specifically, it…

Systems and Control · Electrical Eng. & Systems 2026-03-17 Hui Yin , Xiang Li , Yifan Liu , Weijia Yao

A convergent iterative process is constructed for solving any solvable linear equation in a Hilbert space.

Numerical Analysis · Mathematics 2007-05-23 A. G. Ramm

Constrained non-convex optimization problems frequently arise in control applications. Solving such problems is inherently challenging, as existing methods often converge to suboptimal local minima or incur prohibitive computational costs.…

Optimization and Control · Mathematics 2026-01-27 Anran Li , John P. Swensen , Mehdi Hosseinzadeh