Journal article
Distributed stochastic MPC of linear systems with additive uncertainty and coupled probabilistic constraints
- Abstract:
- This paper develops a new form of distributed stochastic model predictive control (DSMPC) algorithm for a group of linear stochastic subsystems subject to additive uncertainty and coupled probabilistic constraints. We provide an appropriate way to design the DSMPC algorithm by extending a centralized SMPC (CSMPC) scheme. To achieve the satisfaction of coupled probabilistic constraints in a distributed manner, only one subsystem is permitted to optimize at each time step. In addition, by making explicit use of the probabilistic distribution of the uncertainties, probabilistic constraints are converted into a set of deterministic constraints for the predictions of nominal models. The distributed controller can achieve recursive feasibility and ensure closed-loop stability for any choice of update sequence. Numerical examples illustrate the efficacy of the algorithm.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 386.1KB, Terms of use)
-
- Publisher copy:
- 10.1109/TAC.2016.2612822
Authors
+ National Natural Science Foundation of China
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- Grant:
- Foundation for Innovative Research Groups under Grant 61321002
+ National
Natural Science Foundation of China
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- Grant:
- Grant61603041,Grant61225015, Grant61105092
- Grant61422102
+ National Basic Research
Program of China
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- Grant:
- 973 Program) under Grant 2012CB720000
- Publisher:
- IEEE
- Journal:
- IEEE Transactions on Automatic Control More from this journal
- Volume:
- 62
- Issue:
- 7
- Pages:
- 3474-3481
- Publication date:
- 2016-01-01
- DOI:
- EISSN:
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1558-2523
- ISSN:
-
0018-9286
- Keywords:
- Pubs id:
-
pubs:676059
- UUID:
-
uuid:831a044d-2f99-490d-8487-d719b9650982
- Local pid:
-
pubs:676059
- Source identifiers:
-
676059
- Deposit date:
-
2017-02-07
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2016
- Notes:
- Copyright © 2016 IEEE. This is the accepted manuscript version of the article. The final version will be available online from IEEE at: https://doi.org/10.1109/TAC.2016.2612822
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