Zur Hauptnavigation wechseln Zur Suche wechseln Zum Hauptinhalt wechseln

Dynamic uncertainties in model predictive control: Guaranteed stability for constrained linear systems

Lukas Schwenkel, Johannes Kohler, Matthias Müller, Frank Allgower

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Abstract

In this work, we propose a tube-based model predictive control (MPC) scheme for state and input constrained linear systems that are subject to dynamic uncertainties de-scribed by integral quadratic constraints (IQCs). We extend the framework of verifying exponential decay rates with IQCs in order to derive an exponentially stable scalar system that bounds the error between the nominal prediction model and the actual unknown system. In the proposed MPC scheme, this error bounding system is predicted together with the nominal model to define the size of the tube. We prove that this scheme achieves robust constraint satisfaction and input-to-state stability, and we demonstrate the flexibility of dynamic tubes in a numerical example.

OriginalspracheEnglisch
Titel des Sammelwerks2020 59th IEEE Conference on Decision and Control, CDC 2020
Seiten1235-1241
Seitenumfang7
ISBN (elektronisch)9781728174471
DOIs
PublikationsstatusVeröffentlicht - 2020
Veranstaltung2020 59th IEEE Conference on Decision and Control (CDC) - Jeju, Südkorea
Dauer: 14 Dez. 202018 Dez. 2020

Publikationsreihe

NameProceedings of the IEEE Conference on Decision and Control
Band2020-December
ISSN (Print)0743-1546
ISSN (elektronisch)2576-2370

Konferenz

Konferenz2020 59th IEEE Conference on Decision and Control (CDC)
Land/GebietSüdkorea
OrtJeju
Zeitraum14 Dez. 202018 Dez. 2020

ASJC Scopus Sachgebiete

  • Steuerung und Optimierung
  • Steuerungs- und Systemtechnik
  • Modellierung und Simulation

Dieses zitieren