Subject description - AE3M35OFD
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Explanatory Notes
Instructions
Web page:
http://dce.fel.cvut.cz/studium/estimation-filtering-and-detection
Anotation:
This course will cover description of the uincertainty of hidden variables (parameters and state of a dynamic system) using the probability language and methods for their estimation. Based on bayesian prblem formulation principles of rational behsavour under uncertainty will be analysed and used to develp algorithms for estimation of parameters of ARX models and Kalman filtering including the extensions.
We will demonstrate numerically robust implementation of the algorithms applicable in real life problems for the areas of industrial process control, robotics and avionics. We will extend the methods for linear gaussian systems to a more generic problems using Monte Calro approach. The course will also cover multimodel approach and its use for the fault detection and isolation and introduction to adaptive control.
Course outlines:
| 1. | | Problem formulation, estimation methods |
| 2. | | Bayesian approach to uncertainty description |
| 3. | | Dynamic system model, probabilistic state definition |
| 4. | | Identification of ARX model parameters |
| 5. | | Tracking of time varuing parameters, forgetting, role of prior informaiton. |
| 6. | | Numerically robust implementaiton for real time parameter tracking |
| 7. | | Stochastic system, Kalman filter. |
| 8. | | Kalman filtr for colour noise, extended Kalman filter, adaptive Kalman filter. |
| 9. | | Stochastic dynamic programming, certainty equivalence principle. |
| 10. | | Adaptive control, cautious and certainty equivalent strategies, dual control. |
| 11. | | Probabilistic method for fault detection and isolation |
| 12. | | Utilizaiton of multiple models |
| 13. | | Nonlinear estimation, local approximation |
| 14. | | Global aproximation, Monte Carlo Kalman filter |
Exercises outline:
Laboratory covers work on individual assignments/projects.
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Literature:
Literatura:
| 1. | | Frank L. Lewis, Lihua Xie, and Dan Popa : Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, CRC Press, 2005 |
Requirements:
Subject is included into these academic programs:
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| Page updated 20.4.2024 11:50:56, semester: L/2023-4, Z/2024-5, Z/2023-4, Send comments about the content to the Administrators of the Academic Programs |
Proposal and Realization: I. Halaška (K336), J. Novák (K336) |