The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Constrained state estimation for nonlinear discrete-time systems: stability and moving horizon approximations
Abstract
State estimator design for a nonlinear discrete-time system is a challenging problem, further complicated when additional physical insight is available in the form of inequality constraints on the state variables and disturbances. One strategy for constrained state estimation is to employ online optimization using a moving horizon approximation. We propose a general theory for constrained moving horizon estimation. Sufficient conditions for asymptotic and bounded stability are established. We apply these results to develop a practical algorithm for constrained linear and nonlinear state estimation. Examples are used to illustrate the benefits of constrained state estimation. Our framework is deterministic.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
(1995) · Cited by 10,558
Constrained model predictive control: Stability and optimality
Mayne, D. Q., Rawlings, J. B., Rao, C. V., & Scokaert, P. O. M. (2000) · Automatica · doi:10.1016/s0005-1098(99)00214-9 · Cited by 8,736
Self-citationStochastic Processes and Filtering Theory
(1970) · Mathematics in Science and Engineering · doi:10.1016/s0076-5392(09)x6022-4 · Cited by 7,302
Robust receding horizon control of constrained nonlinear systems
Michalska, H., & Mayne, D. Q. (1993) · IEEE Transactions on Automatic Control · doi:10.1109/9.262032 · Cited by 1,181
Self-citationH/sup ∞/-0ptimal Control and Related Minimax Design Problems: A Dynamic Game Approach
Basar, T., & Bernhard, P. (1996) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1996.536519 · Cited by 1,047
H∞-Optimal Control and Related Minimax Design Problems
Başar, T., & Bernhard, P. (2008) · Birkhäuser Boston eBooks · doi:10.1007/978-0-8176-4757-5 · Cited by 1,043
Keerthi, S. S., & Gilbert, E. G. (1988) · Journal of Optimization Theory and Applications · doi:10.1007/bf00938540 · Cited by 824
Suboptimal model predictive control (feasibility implies stability)
Scokaert, P. O. M., Mayne, D. Q., & Rawlings, J. B. (1999) · IEEE Transactions on Automatic Control · doi:10.1109/9.751369 · Cited by 614
Self-citationOn the estimation of state variables and parameters for noisy dynamic systems
Cox, H. (1964) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1964.1105635 · Cited by 475
A moving horizon‐based approach for least‐squares estimation
Robertson, D. G., Lee, J. H., & Rawlings, J. B. (1996) · AIChE Journal · doi:10.1002/aic.690420811 · Cited by 352
Self-citation
Cited by
AcinoSet: A 3D Pose Estimation Dataset and Baseline Models for Cheetahs in the Wild
Joska, D., Clark, L., Muramatsu, N., Jericevich, R., Nicolls, F., Mathis, A., Mathis, M. W., & Patel, A. (2021) · 2021 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra48506.2021.9561338 · Cited by 66
Metadata
- Authors
- Rao, C. V., Rawlings, J. B., & Mayne, D. Q.
- Venue
- IEEE Transactions on Automatic Control
- Published
- 2003-02
- Volume
- 48
- Issue
- 2
- Pages
- 246-258
- ISSN
- 0018-9286 (ISSN-L)
- OpenAlex
- W2143558629
- Cited by
- 894
- References
- 25
- FWCI
- 39.23
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Constrained state estimation for nonlinear discrete-time systems: stability and moving horizon approximations. https://app.cochat.ai/papers/10.1109/tac.2002.808470
- The paper
- Rao, C. V., Rawlings, J. B., & Mayne, D. Q. (2003). Constrained state estimation for nonlinear discrete-time systems: stability and moving horizon approximations. IEEE Transactions on Automatic Control. https://doi.org/10.1109/tac.2002.808470
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.