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Fakultät BCI

Data-Based Dynamic Modeling

Type Lecture (1 SWS) + Exercise (1 SWS)
Rhythm Summer Semester
Audience Bachelor BIW, CIW
Master BIW, CIW, PSE
Language English
LV number 061612
LSF number 061613

Please refer to the LFS for the most recent information.

Course content

The course which is taught in English covers the following topics:

Identification of simple models from step responses. Parameter identification: Basic idea, mathematical description of sampled systems, AXR, ARMAX and OE estimation. Modeling using nonlinear black box models (perceptron neural nets, radial-basis-function nets), training. Structures of dynamic nonlinear black box models, quality of neural net models. Model errors: Sources of errors, limits of model accuracy, model accuracy and controller performance.

Acquired competences

The students can identify the dominant dynamics of a process from step responses and can apply modern methods and algorithms to identify the parameters of linear process models from measured data. They understand the concept of sufficient excitation and the sources of errors in parameter estimation. The students understand the structure of nonlinear black box models and can judge the quality and the limitations of data-based models.


Exam Written (120 min) / Oral (30 min) + Graded Homework
Preliminaries Mathematik 1, Mathematik 2, Einführung in die Programmierung.
Knowledge of the course "Prozessdynamik und Regelung / Introduction to Process Dynamics and Control"
Literature The slides of the course and any additional materials such as literature lists and website recommendations will be published in the virtual workrooms in Moodle provided for this purpose. Details will be announced at the beginning of the course.

Only the information found in the LSF and the most recent edition of the Modulhandbuch der Fakultät
Bio – und Chemieingenieurwesen is binding. The content on this page may not reflect the most up-to-date information.