A distributed active set method for model predictive control

Publikationstyp
Conference Paper
Date Issued
2021-06-01
Sprache
English
Author(s)
Stomberg, Gösta  
Engelmann, Alexander
Faulwasser, Timm  
TORE-URI
https://hdl.handle.net/11420/46163
Journal
IFAC-PapersOnLine  
Volume
54
Issue
3
Start Page
263
End Page
268
Citation
IFAC-PapersOnLine 54 (3): 263-268 (2021)
Contribution to Conference
16th IFAC Symposium on Advanced Control of Chemical Processes, ADCHEM 2021  
Publisher DOI
10.1016/j.ifacol.2021.08.252
Scopus ID
2-s2.0-85117940748
Publisher
IFAC
This paper presents a novel distributed active set method for model predictive control of linear systems. The method combines a primal active set strategy with a decentralized conjugate gradient method to solve convex quadratic programs. An advantage of the proposed method compared to existing distributed model predictive algorithms is the primal feasibility of the iterates. Numerical results show that the proposed method can compete with the alternating direction method of multipliers in terms of communication requirements for a chain of masses example.
Subjects
Active set methods
ADMM
Conjugate gradient methods
Distributed control
Model predictive control
DDC Class
004: Computer Sciences
510: Mathematics