Types of models, physics/ mechanics/ electronics- overview, model somplifications, bond graphs, object oriented modelling, disturbance and disturbance models, non- parametric identification, parameter estimation, system identification for modelling.
Simulation: numerical errors, computer simulation tools.
After completed course the student should be able to derive mathematical models for technical systems based on fundamental physical relations and based on measurement data.
In particular, after completing the course the student should be able to:
- Derive mathematical models of technical systems based on fundamental physical relations.
- Employ systematic and object- oriented based modelling tools to develop models of systems with subparts from different physical domains.
- Describe how differential-algebraic equations (DAEs) arise in modelling of technical systems.
- Choose a proper numerical solver and its parameters for effective simulation of a given problem.
- Estimate impulse and frequency responses as well as transfer- functions for linear systems based on measured input and output data.
- Analyze the statistical properties of basic estimation methods, and explain the practical consequences of these results.
- Choose appropriate experimental conditions to collect data for system identification.
- Use the most common methods for model validation agains experimental data.