Conference item
Adaptive model predictive control with robust constraint satisfaction
- Abstract:
- Adaptive control for constrained, linear systems is addressed and a solution based on Model Predictive Control (MPC) and set-membership system identification is presented. The paper introduces a computationally tractable solution which uses observations of past state and input trajectories to update the model and improve control performance while maintaining guaranteed constraint satisfaction and recursive feasibility. The developed approach is applied to a stabilizing MPC scheme and practical stability under persistent, additive disturbance is proved. A numerical example and brief comparison with non-adaptive MPC is provided.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 291.7KB, Terms of use)
-
- Publisher copy:
- 10.1016/j.ifacol.2017.08.512
Authors
+ German Research Foundation
More from this funder
- Funding agency for:
- Lorenzen, M
- Allgöwer, F
- Grant:
- EXC 310/2
- EXC 310/2
- Publisher:
- Elsevier
- Host title:
- IFAC-PapersOnLine
- Journal:
- IFAC-PapersOnLine More from this journal
- Volume:
- 50
- Issue:
- 1
- Pages:
- 3313-3318
- Publication date:
- 2017-10-18
- Acceptance date:
- 2017-02-27
- Event location:
- Toulouse, France
- DOI:
- ISSN:
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2405-8963
- Pubs id:
-
pubs:744772
- UUID:
-
uuid:efcbf50f-ad5f-432d-850b-a099da780c33
- Local pid:
-
pubs:744772
- Source identifiers:
-
744772
- Deposit date:
-
2017-12-01
Terms of use
- Copyright holder:
- © 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd
- Copyright date:
- 2017
- Notes:
- This is a conference paper presented at the 20th IFAC World Congress, 9-14 July 2017, Toulouse, France. This is the author accepted manuscript following peer review version of the article. The final version is available online from Elsevier at: 10.1016/j.ifacol.2017.08.512
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