Conference item
Distributed stochastic MPC of linear systems with parameter uncertainty and disturbances
- 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 offl...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Accepted manuscript, pdf, 474.9KB)
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- Publisher copy:
- 10.1109/ChiCC.2016.7554022
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Authors
Funding
+ National Natural Science
Foundation of China
More from this funder
Grant:
61321002
61225015
61105092
Bibliographic Details
- Publisher:
- Technical Committee on Control Theory Publisher's website
- Journal:
- Proceedings of the ,5th Chinese Control Conference Journal website
- Pages:
- 4312-4317
- Host title:
- 2016 35th Chinese Control Conference (CCC)
- Publication date:
- 2016-08-29
- Acceptance date:
- 2016-04-01
- DOI:
- EISSN:
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1934-1768
- Source identifiers:
-
629612
- ISBN:
- 9789881563910
Item Description
- Keywords:
- Pubs id:
-
pubs:629612
- UUID:
-
uuid:f18a045e-09c8-427b-b01b-29d07fa575ec
- Local pid:
- pubs:629612
- Deposit date:
- 2016-06-24
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2016
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from IEEE at: http://dx.doi.org/10.1109/ChiCC.2016.7554022
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