- Di Ruscio, D. (2002).Subspace system
identification.Theory and applications. Lecture notes
(pdf-file).
- State estimation and the Kalman filter. Lecture notes
(pdf-file). 21 pages. We skip sections 2.1, 2.3, 2.4 and
2.5.
- Further notes on the state
observer. MATLAB files: Function to find the gain,
K:
lpe2.m
lpe.m,
ss2ocf.m. Solution ex. 5.1:
ex_id_simp2.m File to generate input experiment:
prbs1.m
- Prediction error methods. Chapter 14 lecture notes.
(pdf-file). Directly from this file: Ch. 14
- Di Ruscio, D. (2005). Subspace system identification
of the Kalman filter: Open and closed loop systems. Paper
- Di Ruscio, D- (2001). An introduction to MATrix
LABoratory (MATLAB). Lecture
notes
- Additional support lecture notes on System
Identification, Ljung (1995)
- Development of System Identification. Ljung (1996).
- A view on the Unscented Kalman Filter (UKF) algorithm
and comparison with the Extended Kalman Filter (EKF). Paper
-
Closed and Open
Loop Subspace System Identication of the Kalman
Filter
The course syllabus is mainly taken from
enumerate: 1 and 5 (subspace system identification),
2 and 3 (state estimation and Kalman filter) and 4
(prediction error methods for system identification). See
also the Lecture Plan for details. Item 7 and 8 gives an
additional overview of the field of System identification.
For possible post-script files: Notes about how to read
post script (*.ps) files and to covert from ps-files to
pdf-files (use Gsview):
- Post-script (*.ps) files can be read and printed to
our post script printers by the gsview software. Note. A
new version of gsview is available and may be downloaded
from the internet.
Faglærer: Dr. ing., 1. amanuensis David Di
Ruscio
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