| 1 |
Models and model types |
1-3 |
lecture
1 |
| 2 |
Principles for model building |
4, 5 |
lecture 2 |
| 3 |
DAE models, modeling tools and simulation |
7, 8, 18 |
lecture 3 |
| 4 |
Discrete time, signals and disturbances |
9 |
lecture 4 |
| 5 |
Non-parametric identification |
10 |
lecture 5 |
| 6 |
Static linear regression and statistical analysis |
11.1-11.6 |
lecture 6 |
| 7 |
Parametric identification |
12.1-12.5 |
lecture 7 |
| 8 |
Validation, regularization and statistical properties |
12.6-12.9 |
lecture
8 |
| 9 |
Subspace methods |
13 |
lecture 9 |
| 10 |
Closed-loop system identification |
|
lecture
10 |
| 11 |
Nonlinear identification |
14, 15 |
lecture 11 |
| 12 |
Identification in practice |
16, 17, 19 |
lecture 12 |