This title appears in the Scientific Report :
2016
Please use the identifier:
http://dx.doi.org/10.1109/TAC.2015.2471775 in citations.
Convergence and Stability of a Constrained Partition-Based Moving Horizon Estimator
Convergence and Stability of a Constrained Partition-Based Moving Horizon Estimator
A novel type of iterative partition-based moving horizon estimators (PMHE) is proposed, the estimates of which approach those of a centralized moving horizon estimator as the number of iterations increases. It uses a deterministic setting and can handle known inputs as well as bounds on the estimate...
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Personal Name(s): | Schneider, Rene |
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Marquardt, Wolfgang | |
Contributing Institute: |
Vorstandsbereich Wissenschaft, Außenbeziehungen; VS-V |
Published in: | IEEE transactions on automatic control, 61 (2016) 5, S. 1316 - 1321 |
Imprint: |
New York, NY
Institute of Electrical and Electronics Engineers
2016
|
DOI: |
10.1109/TAC.2015.2471775 |
Document Type: |
Journal Article |
Research Program: |
ohne Topic |
Publikationsportal JuSER |
A novel type of iterative partition-based moving horizon estimators (PMHE) is proposed, the estimates of which approach those of a centralized moving horizon estimator as the number of iterations increases. It uses a deterministic setting and can handle known inputs as well as bounds on the estimated state. We derive conditions on the system, its partitions, and the scalar regularization parameter, which guarantee convergence towards the optimal centralized state estimate as well as stability of the estimation error dynamics, even with a finite number of iterations at each time step. Finally, numerical simulations demonstrate both the features and competitive estimation quality of the proposed method. |