Type of Course: Presence (details in moodle course)

Date: fridays 12:00-14:45 (12:00-13:30 lecture, 14:00-14:45 Exercise)

Room: BA 127

As of winter semester 2024/25

After an introduction into goals and significance of modelling and simulation, numerical methods for solving ordinary differential equations (various implicit and explicit single step and multi-step methods, other methods) and their properties (numeric stability, local and global errors, suitability for stiff differential equations, for step inputs and for step width control) are considered. For the solution of partial differential equations, there is only a hint by an example with spce and time discretization.

The chapter "experimental modelling" at first discusses principles and choice of test signals, followed by methods for gaining nonparametric models. For general parmeter estimation methods, as they are contained in the MATLAB system identification toolbox, the basic models are presented. For one method, the reduction to a least-squares problem is shown; for further details the lecture refers to another lecture ("state and parameter estimation"). Subspace methods and identification of nonlinear systems are only mentioned as outlook.

A short overview over physical fundamentals from mechanics, thermodynamics and fluid dynamics is given. These fundamentals are applied for theoretical modelling (gaining rigorous models) for numerous examples, e.g.:

• DC drive, pump and compressor, valve, heat exchanger, heated vessel (liquid, gas, boiling liquid and vapour), stirring vessel reactor with chemical reaction.