An online convex optimization algorithm for controlling linear systems with state and input constraints

This paper studies the problem of controlling linear dynamical systems subject to point-wise-in-time constraints. We present an algorithm similar to online gradient descent, that can handle time-varying and a priori unknown convex cost functions while restraining the system states and inputs to poly...

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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Nonhoff, Marko, Müller, Matthias A
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 16.03.2021
Subjects:	Algorithms Computational geometry Convexity Cost function Linear systems Optimization
ISSN:	2331-8422
Online Access:	Get full text
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