Scalable robust output feedback MPC of linear sampled-data systems

Felix Gruber, Matthias Althoff

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Cyber-physical control systems typically consist of two components: a clocked digital controller and a physical plant evolving in continuous time. Clearly, the state and input constraints must be satisfied not only at, but also between sampling times of the controller. We address this issue by proposing a robust output feedback model predictive control approach for sampled-data systems, which are affected by additive disturbances and measurement noise. To guarantee robust constraint satisfaction for an infinite time horizon, we present a scalable approach to compute safe terminal sets. Based on these sets and using scalable reachability analysis and convex optimization algorithms, we construct real-time controllers that explicitly consider all online computation times. We demonstrate the usefulness of our robust control approach using a vehicle platooning benchmark from the literature.

Original languageEnglish
Title of host publication60th IEEE Conference on Decision and Control, CDC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2563-2570
Number of pages8
ISBN (Electronic)9781665436595
DOIs
StatePublished - 2021
Event60th IEEE Conference on Decision and Control, CDC 2021 - Austin, United States
Duration: 13 Dec 202117 Dec 2021

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2021-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference60th IEEE Conference on Decision and Control, CDC 2021
Country/TerritoryUnited States
CityAustin
Period13/12/2117/12/21

Fingerprint

Dive into the research topics of 'Scalable robust output feedback MPC of linear sampled-data systems'. Together they form a unique fingerprint.

Cite this