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We analyze a zeroth-order particle algorithm for the global optimization of a non-convex function, focusing on a variant of Consensus-Based Optimization (CBO) with small but fixed noise intensity. Unlike most previous studies restricted to…

Optimization and Control · Mathematics 2025-11-24 Pascal Bianchi , Radu-Alexandru Dragomir , Victor Priser

In this paper, we study two kinds of singular optimal controls (SOCs for short) problems where the systems governed by forward-backward stochastic differential equations (FBSDEs for short), in which the control has two components: the…

Optimization and Control · Mathematics 2020-12-22 Liangquan Zhang

This paper presents a nonlinear control algorithm for speed control of a permanent magnet motor. The idea relies on a feedback linearization technique which also ensures adherence to current and voltage bounds. These bounds arise from…

Systems and Control · Electrical Eng. & Systems 2019-11-27 Shravan Mohan

By enabling constraint-aware online model adaptation, model predictive control using Gaussian process (GP) regression has exhibited impressive performance in real-world applications and received considerable attention in the learning-based…

Optimization and Control · Mathematics 2024-09-17 Amon Lahr , Andrea Zanelli , Andrea Carron , Melanie N. Zeilinger

We prove the convergence of the fixed-point (also called thresholding) algorithm in three optimal control problems under large volume constraints. This algorithm was introduced by C\'ea, Gioan and Michel, and is of constant use in the…

Optimization and Control · Mathematics 2023-06-27 Antonin Chambolle , Idriss Mazari-Fouquer , Yannick Privat

Following Demidovich's concept and definition of convergent systems, we analyze the optimal nonlinear damping control, recently proposed [1] for the second-order systems. Targeting the problem of output regulation, correspondingly tracking…

Systems and Control · Electrical Eng. & Systems 2021-06-03 Michael Ruderman

In connection with the optimization problem $$\inf_{x\in argmin \Psi}\{\Phi(x)+\Theta(x)\},$$ where $\Phi$ is a proper, convex and lower semicontinuous function and $\Theta$ and $\Psi$ are convex and smooth functions defined on a real…

Optimization and Control · Mathematics 2016-03-16 Radu Ioan Bot , Ernö Robert Csetnek

We consider the problem of synthesizing optimal linear feedback policies subject to arbitrary convex constraints on the feedback matrix. This is known to be a hard problem in the usual formulations ($\Htwo,\Hinf,\LQR$) and previous works…

Systems and Control · Computer Science 2013-10-28 Krishnamurthy Dvijotham , Emanuel Todorov , Maryam Fazel

We develop a novel unified randomized block-coordinate primal-dual algorithm to solve a class of nonsmooth constrained convex optimization problems, which covers different existing variants and model settings from the literature. We prove…

Optimization and Control · Mathematics 2021-10-29 Quoc Tran-Dinh , Deyi Liu

In this paper, a quadratic optimal control problem is considered for second-order parabolic PDEs with homogeneous Dirichlet boundary conditions, in which the "point" control function (depending only on time) constitutes a source term. These…

Systems and Control · Electrical Eng. & Systems 2024-07-04 Gilberto O. Corrêa , Marlon M. López-Flores , Alexandre L. Madureira

Model predictive control solves a constrained optimization problem online in order to compute an implicit closed-loop control policy. Recursive feasibility -- guaranteeing that the optimal control problem will have a solution at every time…

Optimization and Control · Mathematics 2024-10-16 Jacob W. Knaup , Panagiotis Tsiotras

Optimal control problems involving hybrid binary-continuous control costs are challenging due to their lack of convexity and weak lower semicontinuity. Replacing such costs with their convex relaxation leads to a primal-dual optimality…

Optimization and Control · Mathematics 2017-02-27 Christian Clason , Kazufumi Ito , Karl Kunisch

Mathematical optimization is one of the cornerstones of modern engineering research and practice. Yet, throughout all application domains, mathematical optimization is, for the most part, considered to be a numerical discipline.…

Optimization and Control · Mathematics 2024-01-09 Adrian Hauswirth , Zhiyu He , Saverio Bolognani , Gabriela Hug , Florian Dörfler

We consider a continuous time stochastic optimal control problem under both equality and inequality constraints on the expectation of some functionals of the controlled process. Under a qualification condition, we show that the problem is…

Optimization and Control · Mathematics 2021-07-09 Laurent Pfeiffer , Xiaolu Tan , Yulong Zhou

We consider the internal control of linear parabolic equations through on-off shape controls, i.e., controls of the form $M(t)\chi_{\omega(t)}$ with $M(t) \geq 0$ and $\omega(t)$ with a prescribed maximal measure. We establish small-time…

Optimization and Control · Mathematics 2024-01-09 Camille Pouchol , Emmanuel Trélat , Christophe Zhang

We consider the closely related problems of bandit convex optimization with two-point feedback, and zero-order stochastic convex optimization with two function evaluations per round. We provide a simple algorithm and analysis which is…

Machine Learning · Computer Science 2015-08-03 Ohad Shamir

We study the complexity of optimizing highly smooth convex functions. For a positive integer $p$, we want to find an $\epsilon$-approximate minimum of a convex function $f$, given oracle access to the function and its first $p$ derivatives,…

Optimization and Control · Mathematics 2021-12-06 Ankit Garg , Robin Kothari , Praneeth Netrapalli , Suhail Sherif

In the framework of real Hilbert spaces we study continuous in time dynamics as well as numerical algorithms for the problem of approaching the set of zeros of a single-valued monotone and continuous operator $V$. The starting poin is a…

Optimization and Control · Mathematics 2024-02-23 Radu Ioan Bot , Ernö Robert Csetnek , Dang-Khoa Nguyen

We propose a novel second-order ODE as the continuous-time limit of a Riemannian accelerated gradient-based method on a manifold with curvature bounded from below. This ODE can be seen as a generalization of the ODE derived for Euclidean…

Optimization and Control · Mathematics 2020-03-10 Foivos Alimisis , Antonio Orvieto , Gary Bécigneul , Aurelien Lucchi

We describe a reformulation (following Hales (2017)) of a 1934 conjecture of Reinhardt on pessimal packings of convex domains in the plane as a problem in optimal control theory. Several structural results of this problem including its…

Optimization and Control · Mathematics 2022-08-10 Koundinya Vajjha
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