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A moving horizon‐based approach for least‐squares estimation
Abstract
A general formulation of the moving horizon estimator is presented. An algorithm with a fixed‐size estimation window and constraints on states, disturbances, and measurement noise is developed, and a probabilistic interpretation is given. The moving horizon formulation requires only one more tuning parameter (horizon size) than many well‐known approximate nonlinear filters such as extended Kalman filter (EFK), iterated EKF, Gaussian second‐order filter, and statistically linearized filter. The choice of horizon size allows the user to achieve a compromise between the better performance of the batch least‐squares solution and the reduced computational requirements of the approximate nonlinear filters. Specific issues relevant to linear and nonlinear systems are discussed with comparisons made to the Kalman filter, EKF, and other recursive and optimization‐based estimation schemes.
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Citations
Cites
A New Approach to Linear Filtering and Prediction Problems
Kalman, R. E. (1960) · Journal of Basic Engineering · doi:10.1115/1.3662552 · Cited by 31,751
Cited by
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-citationModel predictive control: past, present and future
Morari, M., & H. Lee, J. (1999) · Computers & Chemical Engineering · doi:10.1016/s0098-1354(98)00301-9 · Cited by 2,335
Rao, C. V., Rawlings, J. B., & Mayne, D. Q. (2003) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2002.808470 · Cited by 894
Self-citationSoft sensing of intracellular states for CHO cell bioprocessing with Ensemble Kalman Filters
Yu, L., del Rio Chanona, A., & Kontoravdi, C. (2026) · Journal of Process Control · doi:10.1016/j.jprocont.2026.103875
Metadata
- Authors
- Robertson, D. G., Lee, J. H., & Rawlings, J. B.
- Venue
- AIChE Journal
- Publisher
- Wiley
- Published
- 1996-08
- Volume
- 42
- Issue
- 8
- Pages
- 2209-2224
- ISSN
- 0001-1541 (ISSN-L)
- 1547-5905
- OpenAlex
- W2057184806
- Cited by
- 352
- References
- 1
- FWCI
- 13.94
- Type
- journal article
- Language
- en
- Open access
- closed
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- Robertson, D. G., Lee, J. H., & Rawlings, J. B. (1996). A moving horizon‐based approach for least‐squares estimation. AIChE Journal. https://doi.org/10.1002/aic.690420811
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