- Abstract:
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In this paper, we propose a distributed stochastic model predictive control (DSMPC) algorithm for a team of linear subsystems sharing coupled probabilistic constraints. Each subsystem is subject to both parameter uncertainty and stochastic disturbances. To handle the probabilistic constraints, we first decompose the state trajectory into a nominal part and an uncertain part. The latter one is further divided into two parts: one is bounded by probabilistic tubes that are calculated offline by ...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Accepted manuscript
- Files:
-
-
(pdf, 470.2KB)
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- Publisher copy:
- 10.1109/ChiCC.2016.7554022
-
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- Publisher:
- Institute of Electrical and Electronics Engineers Publisher's website
- Volume:
- 2016-August
- Pages:
- 4312-4317
- Publication date:
- 2016-08-05
- Acceptance date:
- 2016-04-01
- DOI:
- ISSN:
-
1934-1768 and 2161-2927
- Pubs id:
-
pubs:629612
- URN:
-
uri:bb19585a-cc0c-4dfe-a399-e666ec2f3455
- UUID:
-
uuid:bb19585a-cc0c-4dfe-a399-e666ec2f3455
- Local pid:
- pubs:629612
- ISBN:
- 9789881563910
- Copyright holder:
- Institute of Electrical and Electronics Engineers
- Copyright date:
- 2016
- Notes:
- © Copyright 2017 IEEE - All rights reserved
Conference item
Distributed stochastic MPC of linear systems with parameter uncertainty and disturbances
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