Robust distributed model predictive control

AG Richards, JP How

Research output: Contribution to journalArticle (Academic Journal)

212 Citations (Scopus)

Abstract

This paper presents a formulation for distributed model predictive control (DMPC) of systems with coupled constraints. The approach divides the single large planning optimization into smaller sub-problems, each planning only for the controls of a particular subsystem. Relevant plan data is communication between sub-problems to ensure that all decision satisfy the coupled constraints. The new algorithm guarantees that all optimizations remain feasible, that the coupled constraints will be satisfied, and that each subsystem will converge to its target, despite the action of unknown but bounded disturbances. Simulation results are presented showing that the new algorithm offers significant reductions in computation time for only a small degradation in performance in comparison with centralized MPC.
Original languageEnglish
Pages (from-to)1517 - 1531
Number of pages15
JournalInternational Journal of Control
Volume80 (9)
DOIs
Publication statusPublished - Sep 2007

Bibliographical note

Publisher: Taylor & Francis

Fingerprint Dive into the research topics of 'Robust distributed model predictive control'. Together they form a unique fingerprint.

  • Cite this