325.065 Identification - Experimental Modeling
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2020W, UE, 1.0h, 1.0EC
TUWEL

Properties

  • Semester hours: 1.0
  • Credits: 1.0
  • Type: UE Exercise
  • Format: Distance Learning

Learning outcomes

After successful completion of the course, students are able to achieve two targets of data-driven modelling:

  1. For a given application problem with existing measurement data both the selection of a suitable model structure as well as the optimal estimation of the optimal model parameters can be performed. Alternative models can be assessed in a quantitative way and can be validated by state-of-the-art methods.
  2. Advanced literature on methods for system identification can be acquired and implemented idependently.

Subject of course

Contents of the lecture are topics of practical exercises, and the application of dedicated software tools is execised.

Teaching methods

Presentation over live online meetings, presentation of computational examples using MATLAB/Simulink, links to current research projects at the department, discussion of results and alternatives.

The exercise is actually integrated in the respective lecture comprising presentations of computational examples and homeworks.

Mode of examination

Written

Additional information

The exercises will be held in parallel to the lecture as soon as sufficient contents have been presented.

Lecturers

Institute

Examination modalities

Several homeworks similar to the examples done in the lecture are handed out. They have to be completed by the student and handed in at the end of the course.

Course registration

Not necessary

Curricula

Literature

Lecture notes for this course are available (institute 325A5). Further literature references in the script.

Opening hours of the secretary's office: Tuesday, Wednesday and Thursday from 09:00 a.m. till 11:00 a.m.

Due to COVID the institute is not open to students. Please contact the secretary's office via E-Mail oder telephone.

Previous knowledge

Fundamentals of Feedback Control is compulsory and excellent knowledge in the fields of mathematics and stochastics is expected. Especially Digital Control is nice to have although not compulsory.

Preceding courses

Accompanying courses

Continuative courses

Language

German