Moving Horizon Estimation
Simulink and MATLAB Toolbox for Moving Horizon Estimation and Model Predictive Control
You are now following this Submission
- You will see updates in your followed content feed
- You may receive emails, depending on your communication preferences
Moving Horizon Estimation (MHE) is an optimization approach that uses a series of measurements observed over time, containing noise (random variations) and other inaccuracies, and produces estimates of unknown variables or parameters. Unlike deterministic approaches like the Kalman filter, MHE requires an iterative approach that relies on linear programming or nonlinear programming solvers to find a solution.
See http://apmonitor.com/wiki/index.php/Main/Estimation for a tutorial video and information on using these files.
Cite As
John Hedengren (2026). Moving Horizon Estimation (https://au.mathworks.com/matlabcentral/fileexchange/41949-moving-horizon-estimation), MATLAB Central File Exchange. Retrieved .
Acknowledgements
Inspired by: MINLP: Mixed Integer Nonlinear Programming, Model Predictive Control, Optimization, Nonlinear Control, and Estimation Toolbox
General Information
- Version 1.0.0.0 (45.3 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 |
