Conference item
Robust adaptive tube model predictive control
- Abstract:
- An adaptive Model Predictive Control (adaptive MPC) strategy is proposed for linear systems with constant unknown model parameters, bounded additive disturbances and state and control constraints. By combining online set-based identification and robust tube MPC, the proposed controller reduces the conservativeness of constraint handling, guarantees recursive feasibility and provides asymptotic bounds on the closed loop system state that depend explicitly on the the identified parameter set. Computational tractability is ensured by using fixed complexity polytopic sets to bound the model parameters and predicted states. Convex conditions for persistence of excitation are considered. The results are illustrated by a numerical example.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Authors
- Publisher:
- IEEE
- Host title:
- 2019 American Control Conference (ACC)
- Journal:
- 2019 American Control Conference More from this journal
- Pages:
- 3695-3701
- Publication date:
- 2019-08-29
- Acceptance date:
- 2019-01-27
- ISSN:
-
2378-5861
- ISBN:
- 9781538679265
- Pubs id:
-
pubs:983113
- UUID:
-
uuid:02d18ffb-d4ff-4c7f-b793-94ed8c040255
- Local pid:
-
pubs:983113
- Source identifiers:
-
983113
- Deposit date:
-
2019-03-16
Terms of use
- Copyright holder:
- AACC
- Copyright date:
- 2019
- Notes:
- Copyright © 2019 AACC. This is the accepted manuscript version of the article. The final version is available online from IEEE at: https://ieeexplore.ieee.org/document/8814456
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