Constrained process monitoring: Moving‐horizon approach

By C. V. Rao, James B. Rawlings. 2002

203 citations recorded by the source corpus.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/d33a874ed74148956f01a0ea4b7711b5f5e08726

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. D. Simon
2. Eric L. Haseltine
3. James B. Rawlings
4. Lars Grüne
5. Riccardo Scattolini
6. Panagiotis D. Christofides
7. David Q. Mayne
8. Matthew J. Ellis

Citations in the corpus

• Kalman filtering with state constraints: a survey of linear and nonlinear algorithms (2010, methodology): “The approaches that can be used in these cases include second-order expansion of the constraints [22], the smoothly constrained Kalman filter [23], moving horizon estimation [24, 25, 26], various modifications of the unscented Kalman filter [2, 3], interior point approaches [27], and particle filter”
• Critical Evaluation of Extended Kalman Filtering and Moving-Horizon Estimation (2005, methodology): “17,18 We note that the restrictive assumptions of normally distributed noises and the model given by eq 1 are not required by MHE.”