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:	Proceedings of the American Control Conference pp. 2523 - 2528
Main Authors:	Nonhoff, Marko, Muller, Matthias A.
Format:	Conference Proceeding
Language:	English
Published:	American Automatic Control Council 25.05.2021
Subjects:	Control systems Convex functions Cost function Heuristic algorithms Prediction algorithms Solids Time measurement
ISSN:	2378-5861
Online Access:	Get full text
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