Advanced System Identification - Interactive curriculae of TU Ilmenau
The interactive curriculae provide information on the degree programmes offered by the TU Ilmenau.
Please refer to the respective study and examination rules and regulations for the legally binding curricula (Annex Curriculum).
You can find all details on planned lectures and classes in the course catalogue.
Please note that this page is no longer updated. All modules and study plans from PO version 2021 onwards (Bachelor and Master study programs) are now available on the Campus Portal.
| module properties Advanced System Identification in degree program Diplom Elektrotechnik und Informationstechnik 2021 | |
|---|---|
| module number | 200127 |
| examination number | 220485 |
| department | Department of Computer Science and Automation |
| ID of group | 2211 (Automation Engineering) |
| module leader | Prof. Dr. Yuri Shardt |
| term | winter term only |
| language | Englisch |
| credit points | 5 |
| on-campus program (h) | 45 |
| self-study (h) | 105 |
| obligation | elective module |
| exam | examination performance with multiple performances |
| details of the certificate | Das Modul Advanced System Identification mit der Prüfungsnummer 220485 schließt mit folgenden Leistungen ab:
Pass for the labority component |
| link to Moodle course | |
| teacher | Prof. Dr. Shardt, Yuri |
| signup details for alternative examinations | |
| maximum number of participants | |
| previous knowledge and experience | Good understanding of statistics and linear regression (such as that offered in the course System Identification (de: Systemidentification)), calculus, linear algebra, and basic control (such as that offered in the course Control Engineering I) |
| learning outcome | By the end of the course, students should be able to analyse and understand the results from modelling and how to improve the model he has obtained. From the lectures, they will have learnt the theoretical foundation of stochastic modelling, Kalman filters, and process identification of time-varying processes. From the laboratories, they will have learnt how to apply stochastic modelling to real examples using appropriate software. From the lectures and laboratories, the students should have learnt how to develop and implement solutions that require the use of statistics, stochastic modelling, and system identification for real-world problems. They should have learnt to constructively take criticism and implement comments and suggestions from their instructors and fellow students. |
| content | In this course, the students will learn the following topics: |
| media of instruction and technical requirements for education and examination in case of online participation | Presentations, Course notes, and Whiteboard lectures, online according to the regulations of TU Ilmenau, Moodle |
| literature / references | 1. Yuri A.W. Shardt (2022). Statistics for Chemical and Process Engineers: A Modern Approach, 2nd edition, Springer International Publishing: Cham, Switzerland. (430 pp.) ISBN: 978-3-030-83189-9. doi: 10.1007/978-3-030-83190-5. |
| evaluation of teaching | |