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A distributed active set method for model predictive control
Publikationstyp
Conference Paper
Publikationsdatum
2021-06-01
Sprache
English
Author
Enthalten in
Volume
54
Issue
3
Start Page
263
End Page
268
Citation
IFAC-PapersOnLine 54 (3): 263-268 (2021)
Contribution to Conference
Publisher DOI
Scopus ID
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.
Schlagworte
Active set methods
ADMM
Conjugate gradient methods
Distributed control
Model predictive control
DDC Class
004: Computer Sciences
510: Mathematics