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Course Outline

Peter Dannenmann, Georg Fries, Karin Grslund, Patrick Metzler, Michael Schmidt, Andreas Zinnen

Dr. Peter Dannenmann Modelling and Simulation using MATLAB 2

Course Outline

Chapter 1: Modelling and Simulation (starting April 22nd, 2014)

Background information on the applications of simulation techniques

Classification of simulation systems

Basic simulation and modelling techniques

The Model Development Life Cycle

Dr. Georg Fries Modelling and Simulation using MATLAB 3

Course Outline

Chapter 2: Introduction to MATLAB Concepts (starting April 29th, 2014)

The MATLAB User Interface Commands Plotting Numbers Variables, Arrays and Matrices Scripts and Functions Control Flow Examples

Dr. Karin Grslund Modelling and Simulation using MATLAB 4

Course Outline

Chapter 3: Modelling a Business Case (starting May 6th, 2014)

Overview on Modelling Business Cases

Workshop on Design Thinking

Calculating a Business Case

Dr. Patrick Metzler Modelling and Simulation using MATLAB 5

Course Outline

Chapter 4: Methods to Solve Formal Problems (starting May 13th, 2014)

Toolbox for Solving Formal Problems Analogies Definitions Divide and Conquer Exchange of Given and Looked For Plausibility Tests

Brute Force Least Squares Monte Carlo

Dr. Michael Schmidt Modelling and Simulation using MATLAB 6

Course Outline

Chapter 5: Knowledge Management (starting May 20th, 2014)

Knowledge is THE critical factor for successful technological developments.

In simulation and modeling experts need to share their knowledge to achieve synergies. This means explicating tacit knowledge.

As it is a most success-critical resource, we need to find out how we can make knowledge available to the development processes in simulation and modeling.

Modelling and Simulation using MATLAB 7

Elective Chapters Introduction to Simulink Statistics for Image Processing

and Machine Learning

Business Case Applications Instance Based Machine

Learning in a Nutshell

Modelling a Water-Treatment Plant

Control Engineering Applications

Applications of Knowledge Management Techniques

Image Processing in a Nutshell

Course Outline


Course Outline

Application Chapter: Introduction to Simulink

Required Previous Chapters: Chapters 1 to 5 Simulinks concept of modelling mathematical

equations: building blocks representing operations and

connections representing data flow

Introduction to Simulinks libraries Handling signals, combining signals to busses Numerical integration in Simulink Hierarchical structuring of simulation models,

modelling subsystems as building blocks of their own


Course Outline

Application Chapter: Statistics for Image Processing and Machine Learning

Required Previous Chapters: Chapters 1 to 5 Random number generation Bayes' theorem Probability density function

Cumulative distribution function Binomial distribution Gaussian distribution Mixture of Gaussian

Histogram processing Bins, equalization, matching Luminance and chrominance

enhancement

10 Dr. Andreas Zinnen Modelling and Simulation using MATLAB

Required Previous Chapters: Statistics for Image Processing and Machine Learning

k-means clustering k-nearest neighbours

Regression analysis/classification Density estimation

Novelty detection using KDE Nadaraya Watson and Silverman

Cross validation Model evaluation

Course Outline

Application Chapter: Instance Based Machine Learning in a Nutshell


Course Outline

Application Chapter: Modelling a Water Treatment Plant

Required Previous Chapters: Introduction to Simulink

Parameters for describing water quality Subsystems of a Water Treatment Plant

Grit chamber, Coagulation basin, Sedimentation basin, Grit filter, Activated carbon filter, UV-disinfection

Mathematical models for describing the subsystems of a Water Treatment plant

Techniques for describing the water parameters and for implementing the mathematical Models

Modelling the single subsystems in Simulink and integrating the complete model

Dr. Patrick Metzler Modelling and Simulation using MATLAB 12

Course Outline

Application Chapter: Control Engineering Applications

Required Previous Chapters: Introduction to Simulink Feed Forward Control, Feed Back Control

and Logical Control Empirical Setup of Controller parameters

Ziegler Nichols Chien Hrons Reswick

Speed Control of a NXT Robot Drive Position Control of a NXT Robot Drive Distance Control of a NXT Robot


Course Outline

Application Chapter: Image Processing in a Nutshell

Required Previous Chapters: Statistics for Image Processing and Machine Learning

Intensity Transformation Image Negatives, Log Transformations Contrast stretching

Spatial Filtering Neighbourhood Filter masks Smoothing, Sharpening, Unsharp Masking Image Enhancement

Examples

Documents

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