LEARNING OUTCOMES
After completing the course, a student can select proper modeling approaches for specific practical problems, formulate mathematical models of physical systems, construct models of systems using modeling tools such as MATLAB and Simulink, and estimate the parameters of linear and nonlinear static systems and linear dynamic systems from measurement data.
Credits: 5
Schedule: 06.09.2023 - 04.12.2023
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Quan Zhou, Kai Zenger
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
Basic modeling methods, including first principle modeling and data-driven modeling, for both static and dynamic systems: first principle modeling, black-box modeling, basics of regression methods, parameter estimation for static linear and non-linear systems, parameter estimation for linear time-invariant dynamical systems, model validation, and selected advanced topics.
Assessment Methods and Criteria
valid for whole curriculum period:
The final grade will take into acount both the home assignments and the final exam. The actual distribution to be specified.
Workload
valid for whole curriculum period:
Lectures, exercise sessions, independent study and problem solving, home assignments.
Contact hours: 24 + 12 h
Independent study: 99 h
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language : English
Teaching Period : 2022-2023 Autumn I - II
2023-2024 Autumn I - IIapplies in this implementation
Please find the course syllabus here.