Recommended prerequisite for participation in the module

Content, progress and pedagogy of the module

Purpose
To enable students to apply some of theoretical and experimental  modelling methods into their project and simulate the system by means of simulation tools, such as Matlab/Simulink.

Learning objectives

Knowledge

• Must have knowledge of the modelling of some typical physical systems, such as mechatronic systems, flow dynamic systems, energy production/transportation/distribution systems, process systems etc., provision of operating conditions
• Must have insight into the theoretical modelling for dynamic systems, including the principles of mass balance, energy balance and momentum balance
• Must have the knowledge of experimental modelling of linear and non-linear dynamic systems, including the experiment design, data collection and pre-filtering, model structure selection, parameter estimation and model validation
• Must have insight of linearization techniques of nonlinear systems
• Must be able to simulate the obtained mathematical model in some typical simulation environment, such as Matlab/Simulink

Skills

• Shall be able to apply basic theoretical and experimental modelling techniques for modelling dynamic systems and simulating them
• Shall be able to model and analyse some typical dynamical systems, including electrical, mechanical, power and thermo dynamical systems etc.
• Must be able to develop models of dynamic systems in the form of block diagrams and be able to reformulate the equivalent diagrams
• Must be able to linearize a obtained nonlinear system and analyse the difference between the linearized and original systems
• Must be able to simulate the obtained mathematical model of concerned system and analyse the system features within a proper simulation environment

Competences

• Be able to apply the theoretical modelling approach to model some typical physical systems, with an orientation for control design purpose
• Be able to correctly apply the experimental modelling approach for complicated systems, including the proper experiment design, data collation and analysis, selection of model structure and estimation of system parameters, as well as model validation
• Be able to apply Linearization techniques for nonlinear system analysis and simplification

Type of instruction

The programme is based on a combination of academic, problem-oriented and interdisciplinary approaches and organised based on the following work and evaluation methods that combine skills and reflection:

• Lectures
• Classroom instruction
• Project work
• Workshops
• Exercises (individually and in groups)
• Teacher feedback
• Reflection
• Portfolio work

Extent and expected workload

Since it is a 5 ECTS course module, the work load is expected to be 150 hours for the student.

Exam

Exams