Filtering theory with applications to fault detection, isolation, and estimation
The focus of this book is on filtering for linear processes, and its primary goal is to design filters from a class of linear stable unbiased filters that yield an estimation error with the lowest root-mean-square (RMS) norm. Various hierarchical classes of filtering problems are defined based on th...
| Main Author: | |
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| Other Authors: | , |
| Format: | eBook |
| Language: | Inglés |
| Published: |
Boston ; Berlin :
Birkhauser
c2007.
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| Edition: | 1st ed. 2007. |
| Series: | Systems & control.
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| Subjects: | |
| See on Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009461514006719 |
Table of Contents:
- Preliminaries
- A special coordinate basis (SCB) of linear multivariable systems
- Algebraic Riccati equations and matrix inequalities
- Exact disturbance decoupling via state and full information feedback
- Almost disturbance decoupling via state and full information feedback
- Exact input-decoupling filters
- Almost input-decoupled filtering under white noise input
- Almost input-decoupled filtering without statistical assumptions on input
- Optimally (suboptimally) input-decoupling filtering under white noise input—H2 filtering
- Optimally (suboptimally) input-decoupled filtering without statistical information on the input-H? filtering
- Generalized H2 suboptimally input-decoupled filtering
- Generalized H? suboptimally input-decoupled filtering
- Fault detection, isolation, and estimation—exact or almost fault estimation
- Fault detection, isolation, and estimation—optimal fault estimation.
