Modelling and Simulation using MATLAB® - Free online courses by German University Professors

By Prof. Dr.-Ing. Georg Fries https://iversity.org/c/13?r=6bd45

Professor of Digital Signal Processing, Department of Engineering, RheinMain University of Applied Sciences, Wiesbaden

How can I build a robot, construct a space station on Mars or realize an adventurous new business venture? There can be no progress or innovation without modelling and simulation. Now you can learn how to design, prove and plan just about everything.

About this course

Technical progress wouldn’t be possible without modelling and simulation. They are starting point and basis in most cases of research and development. Modelling and simulation make a particular part or feature of the world easier to define, visualize, quantify and understand. Both require identifying and selecting relevant aspects of a situation in the real world and then using different types of models for different aims and defining the best fitting model parameters.

MATLAB is a high-level programming language and an environment for numerical computation and visualization. You can analyse data and create models for a wide range of applications, including signal processing and communications, image and video processing, control engineering and computational finance.

In this course you will learn the basics of modelling and simulation from an interdisciplinary perspective. In addition, we will teach you how to develop models using MALTAB and the block diagram environment Simulink.

Why this MOOC is interdisciplinary

Scientific disciplines have their own ideas about specific types of modelling. Such as conceptual models to better understand the subject, graphical models to visualize the subject, operational models to operationalize and mathematical models to quantify the subject. In this course, our experts from three disciplines look at modelling concepts from various angles:

• Technological view
• Economic perspective
• Importance of knowledge management.

Course Contents

The course is divided in two sections. The first part (A) teaches the basics and is mandatory to all participants. Within the second part of the course (B) you have the opportunity to choose from a catalogue of applications (MOOClets) to work on selected examples.

Part A – Interdisciplinary Introduction to modelling and simulation

• Modelling
• Simulation
• Introduction to MATLAB concepts
• Building a business case
• Methods to solve formal problems
• Knowledge management
• Introduction to Simulink

Part B – Selectable Applications of modelling and simulation (MOOClets)
You can choose three to five applications according to your preference and knowledge from the following catalogue:

• Simulation of a water treatment plant
• Application 'modelling a business base'
• Application 'knowledge management'
• Control engineering I – 'controlling Lego® NXT robots'
• Control engineering II – 'line tracking with Lego® Segway'
• Control engineering III – 'a Segway – how does it work?'
• Image processing I – ‘statistics for image processing and machine learning’
• Image processing II – 'a brief introduction to image processing'
• Image processing III – ‘application of machine learning algorithms in a nutshell'
• Quality measurement of video cameras (lenses and sensors)
• Acoustic simulation of musical instruments
• … (further chapters are planned)

Learning with the MOOC

During the term of the MOOC we will offer video lectures that convey modelling and simulation step by step in a descriptive way. You will exercise the issues in interactive tasks and weekly homework.
The MOOC platform is a networking tool. You can benefit from the peer-to-peer learning and the forum within the course. While not required, we recommend creating learning groups and to engage in the community.
Experimentation and playful learning are part of the MOOC.

Learning Outcomes

• Students are acquainted with the concepts of modelling and simulation from an interdisciplinary point of view
• Students are able to implement and simulate models using MATLAB/Simulink
• Depending on the selected applications in part B of the course students get deeper know how in control engineering, image processing, machine learning, business case modelling, knowledge management and simulation of a water treatment plant.
• Enthusiastic students with only simple programming knowledge get an understanding of the basic MATLAB programming.

Prior Knowledge

Mathematics and physics knowledge of secondary level education and programming knowledge are recommended.

Workload

• Approx. 8-12 hours per week.
• 12 Units including individual selected applications of Part B.
• Experimentation and a deeper look at the topics as you like.