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Distributed stochastic MPC of linear systems with parameter uncertainty and disturbances

Abstract:

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 ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/ChiCC.2016.7554022

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Institution:
University of Oxford
Oxford college:
St John's College
Role:
Author
Publisher:
Institute of Electrical and Electronics Engineers Publisher's website
Journal:
Chinese Control Conference Journal website
Volume:
2016-August
Pages:
4312-4317
Host title:
Chinese Control Conference, CCC
Publication date:
2016-08-01
Acceptance date:
2016-04-01
DOI:
ISSN:
2161-2927 and 1934-1768
Source identifiers:
629612
ISBN:
9789881563910
Keywords:
Pubs id:
pubs:629612
UUID:
uuid:bb19585a-cc0c-4dfe-a399-e666ec2f3455
Local pid:
pubs:629612
Deposit date:
2017-02-07

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