What is the course about?
The main objective of this MOOC is to teach you how to use of Simulink® as a simulation tool suitable for a broad variety of application domains. We will specifically focus on topics of interaction of the simulation models with the real world using Arduino Microcontrollers and Simulink®'s corresponding Arduino Support Package.
First, we will explain modelling and simulation concepts in general and introduce Simulink®. As a first application, we show how a simplified model of a Water Treatment Plant is implemented using Simulink®. We will then use an Arduino microcontroller to access hardware in the real world. We will go on to introduce control engineering techniques using Simulink® and apply these techniques to drive an example system of a ball floating in an airstream.
What will I learn?
By the end of this course, you will be able to implement simulation models using the tool Simulink®. These models can cover applications in the engineering domain and you know methods and technologies to create simulation models of realistic complexity.
In the engineering domain, microcontrollers are frequently used to control some physical system. Therefore, in this course you will also learn how to use an Arduino microcontroller for this purpose and how programmes for such a microcontroller are implemented in Simulink®. You will specifically learn techniques of control engineering by applying them to a technically simple physical system that is yet difficult to control.
What do I need to know?
This course will be taught on an academic level for undergraduate students. Therefore, knowledge in mathematics and physics of at least secondary education level as well as programming knowledge is a prerequisite.
Having already passed our MOOC "Modelling and Simulation using MATLAB" is helpful but not mandatory.
Course Structure
Chapter 1: My first Simulink® model
Chapter 2: Advanced Simulink® modelling
Chapter 3: Modelling a Water Treatment Plant
Chapter 4: The Arduino microcontroller and the corresponding Simulink® support package
Chapter 5: Control Engineering using Simulink®
Chapter 6: Control Engineering using the Arduino
Course instructors
Peter Dannenmann
Professor for Computer Science, Department of Engineering, RheinMain University of Applied Sciences
Peter Dannenmann studied Computer Science at the University of Kaiserslautern. After completing his studies he worked with DaimlerChrysler Aerospace in Bremen (now Astrium Space Transportation), developing software for Failure Detection, Identification and Recovery (FDIR) in Aerospace Systems. This also was the topic of his PhD Thesis.
Subsequently he joined the German Research Center for Artificial Intelligence in Kaiserslautern as a Senior Researcher.
Since 2009 Peter Dannenmann is a Professor for Computer Science in the Department of Engineering at the RheinMain University of Applied Science.
Patrick Metzler
Patrick Metzler joined RheinMain University of Applied Sciences in 2004 as professor for control engineering and computer science. Earlier assignments include positions as group leader and technical lead with Nexpress GmbH and Deere & Company. Nexpress was a joint venture between Heidelberger Druckmaschinen AG and Eastman Kodak Company. Patrick was involved in the development of the Nexpress 2100 (clean sheet development of a digital printing press employing model based design) and the John Deere AutoTrac-system (GPS-steered farm vehicles). He holds a Ph.D. and a diploma in Electrical Engineering from University of Kaiserslautern. His research interests include control engineering, design of experiments, molecular simulation and electrostatics. Since 2002 Patrick is also a lecturer at ASW, University of Cooperative Education in St. Ingbert.
Georg Fries
Professor of Digital Signal Processing, Department of Engineering, RheinMain University of Applied Sciences, Wiesbaden
Georg Fries studied Electrical Engineering at the Technical University of Darmstadt, where he also received a Ph.D. degree in speech signal processing. Today he is giving lectures on discrete-time signal processing and video technology. Here he has gained significant experience in modelling signal processing concepts in MATLAB. He has worked on multimodal interaction, digital signal processors and text-to-speech. His current interests concern digital photography and active loudspeakers.