700.107 (23S) Basic lab: Simulation technology and Matlab/Simulink
Überblick
- Lehrende/r
- LV-Titel englisch Basic lab: Simulation technology and Matlab/Simulink
- LV-Art Kurs (prüfungsimmanente LV )
- LV-Modell Präsenzlehrveranstaltung
- Semesterstunde/n 2.0
- ECTS-Anrechnungspunkte 2.0
- Anmeldungen 9 (20 max.)
- Organisationseinheit
- Unterrichtssprache Englisch
- LV-Beginn 03.03.2023
- eLearning zum Moodle-Kurs
Zeit und Ort
LV-Beschreibung
Intendierte Lernergebnisse
This lecture is organized around the following key points aiming at providing students with some important and useful basic knowledge in computational engineering. A particular attention is devoted to solving linear and nonlinear mathematical models (e.g. linear and/or nonlinear algebraic equations, linear and/or nonlinear ordinary differential equation, and linear partial differential equations) with MATLAB/SIMULINK. Further some concrete application examples of practical interest are considered in the fields of Transportation engineering, mechatronics, Control systems engineering, and Signal processing (e.g. simulation of microscopic traffic flow (using ODE models), simulation of macroscopic traffic flow (using PDE models), simulation of filters (using transfer functions), Extraction of a Signal embedded in noise (using correlation and auto-correlation principles).
Overall the learning outcomes are summarized by the following nine points:
- Familiarizing students with some theoretical and useful basic knowledge in computational engineering
- Providing an overview of MATLAB and SIMULINK
- Familiarizing students with some important MATLAB commands for computational engineering
- Use of SYMBOLIC CALCULATION TOOLBOX in MATLAB to solve equations analytically (e.g. Linear algebraic equations - Nonlinear algebraic equations - Linear ordinary differential equations - Nonlinear ordinary differential equations)
- Use of MATLAB to solve equations numerically (e.g. - Linear algebraic equations - Nonlinear algebraic equations - Linear ordinary differential equations - Nonlinear ordinary differential equations)
- Use of SIMULINK to solve equations numerically (e.g. - Linear ordinary differential equations - Nonlinear ordinary differential equations)
- Use of MATLAB to solve linear partial differential equations numerically
- Use of SIMULINK to solve linear partial differential equations numerically
- The Runge-Kutta method for solving nonlinear ODEs and nonlinear PDEs
Applications:
1. Traffic flow analysis: Simulation of models in transportation using MATLAB/SIMULINK (e.g. microscopic traffic flow modeled by ordinary differential equations, macroscopic traffic flow modeled by partial differential equations, etc.)
2. Oscillatory systems in engineering: Simulation of control systems, mechanical and electromechanical systems modeled by coupled nonlinear ordinary differential equations (e.g. Pendulum systems, Electrodynamics loudspeakers, dynamics of an airplane, electrical circuits, analog circuits, analog computing, etc.)
3. Synthesis of filters: Derivation of the transfer functions of filters and simulation using MATLAB/SIMULINK (e.g. Low-pass, high-pass, band-pass, and band-rejection/stop filters)
4. Signal processing: Extraction of signals embedded in noise.
Lehrmethodik
1. The slides are available for the entire lecture. These slides are uploaded into the MOODLE system. The entire content of each slide is systematically explained by the lecturer.
- Very important note: The lecturer clearly explains concepts/information in all chapters. The lecturer will be verifying for each concept that at least 75% of students have understood the concept explained. Otherwise, the lecturer will be keeping on explaining the same concept until it is understood by at least 75% of the students.
2. Additional examples that are not included in the slides are suggested by the lecturer to allow a good understanding of the information provided.
3. The slides contain exercises with solutions to allow a good understanding of the contents of each chapter. These solutions are systematically explained (during the lecture) by the lecturer.
- The slides contain exercises with solutions to be solved by students during the lecture (this is part of the oral exam). Students are fully supported/assisted by the lecturer to get correct / accurate solutions to the suggested exercises. This helps to verify whether students have understood the chapters or not.
Inhalt/e
Chapter 1. Introduction to MATLAB
Chapter 2. Solving ordinary differential equations (ODEs) using MATLAB
Chapter 3. Basics of SIMULINK and solutions of ordinary differential equations
Chapter 4. Analytical solutions of algebraic equations, and differential equations using MATLAB
Chapter 5. Modeling and simulation of passive filters: Mathematical modeling of passive filters using ODEs and derivation of the corresponding transfer functions
Chapter 6. Oscillatory systems in engineering: Simulation of complex system- models using MATLAB/SIMULINK
Chapter 7. Traffic flow analysis: Simulation of coupled ODEs and PDEs used for traffic flow modeling in transportation engineering.
Chapter 8. Signal processing: MATLAB codes for the extraction of signals embedded in noise.
Literatur
- Brian R. Hunt, Ronald L. Lipsman, Jonathan M. Rosenberg, Kevin R. Coombes, John E. Osborn, Garrett J. Stuck, „A Guide to MATLAB: For Beginners and Experienced Users“, Cambridge University Press, 2001.
- Pietruszka, and Wolf Diete, „MATLAB und Simulink in der Ingenieurpraxis“, Springer, ISBN 978-3-8351-9074-0, 2006.
- Misza Kalechman, „Practical MATLAB Basics for Engineers (Practical Matlab for Engineers)“, CRC-Press Taylor & Francis, ISBN-13: 978-1420047745, 2008.
Prüfungsinformationen
Beurteilungskriterien/-maßstäbe
The final grade of the lecture (KS) is obtained as follows:
1. Participation in the lecture and answering questions correspond to the oral examination. This is evaluated with 25% of the overall grade of the lecture (KS).
2. All assignments (i.e., homework) correspond to 25% of the overall grade of the lecture (KS).
3. Final projects (to be defined by the lecturer) correspond to 50% of the final grade of the lecture (KS).
Beurteilungsschema
Note BenotungsschemaPosition im Curriculum
- Bachelorstudium Angewandte Informatik
(SKZ: 511, Version: 19W.2)
-
Fach: Informationstechnik
(Wahlfach)
-
8.3 Informationstechnik (
0.0h XX / 12.0 ECTS)
- 700.107 Basic lab: Simulation technology and Matlab/Simulink (2.0h KS / 2.0 ECTS) Absolvierung im 4., 5., 6. Semester empfohlen
-
8.3 Informationstechnik (
0.0h XX / 12.0 ECTS)
-
Fach: Informationstechnik
(Wahlfach)
- Bachelorstudium Angewandte Informatik
(SKZ: 511, Version: 17W.1)
-
Fach: Informationstechnik
(Wahlfach)
-
2.5 Grundlagen und Methoden der Simulationstechnik, mit Grundlagenlabor (
2.0h KS / 3.0 ECTS)
- 700.107 Basic lab: Simulation technology and Matlab/Simulink (2.0h KS / 3.0 ECTS) Absolvierung im 4. Semester empfohlen
-
2.5 Grundlagen und Methoden der Simulationstechnik, mit Grundlagenlabor (
2.0h KS / 3.0 ECTS)
-
Fach: Informationstechnik
(Wahlfach)
- Bachelorstudium Angewandte Informatik
(SKZ: 511, Version: 12W.1)
-
Fach: Informationstechnik
(Wahlfach)
-
Grundlagen und Methoden der Simulationstechnik, mit Grundlagenlabor (
2.0h KU / 3.0 ECTS)
- 700.107 Basic lab: Simulation technology and Matlab/Simulink (2.0h KS / 3.0 ECTS)
-
Grundlagen und Methoden der Simulationstechnik, mit Grundlagenlabor (
2.0h KU / 3.0 ECTS)
-
Fach: Informationstechnik
(Wahlfach)
- Bachelorstudium Informationstechnik
(SKZ: 289, Version: 22W.1)
-
Fach: Grundlagenlabor Informationstechnik
(Wahlfach)
-
10a Ausgewählte 5 Laborübungen aus den angebotenen Grundlagenlaborübungen der Informationstechnik (zu jeweils 2 ECTS-AP) (
0.0h KS / 10.0 ECTS)
- 700.107 Basic lab: Simulation technology and Matlab/Simulink (2.0h KS / 2.0 ECTS) Absolvierung im 3., 4., 5., 6. Semester empfohlen
-
10a Ausgewählte 5 Laborübungen aus den angebotenen Grundlagenlaborübungen der Informationstechnik (zu jeweils 2 ECTS-AP) (
0.0h KS / 10.0 ECTS)
-
Fach: Grundlagenlabor Informationstechnik
(Wahlfach)
- Bachelorstudium Informationstechnik
(SKZ: 289, Version: 22W.1)
-
Fach: Informationstechnische Vertiefung sowie mathematische Ergänzung
(Wahlfach)
-
10b.1 Ausgewählte 2 Laborübungen aus den angebotenen Grundlagenlaborübungen der Informationstechnik (zu jeweils 2 ECTS-AP) (
0.0h KS / 4.0 ECTS)
- 700.107 Basic lab: Simulation technology and Matlab/Simulink (2.0h KS / 2.0 ECTS) Absolvierung im 3., 4., 5., 6. Semester empfohlen
-
10b.1 Ausgewählte 2 Laborübungen aus den angebotenen Grundlagenlaborübungen der Informationstechnik (zu jeweils 2 ECTS-AP) (
0.0h KS / 4.0 ECTS)
-
Fach: Informationstechnische Vertiefung sowie mathematische Ergänzung
(Wahlfach)
- Bachelorstudium Informationstechnik
(SKZ: 289, Version: 22W.1)
-
Fach: Informationstechnische Vertiefung sowie mathematische Ergänzung
(Wahlfach)
-
10b.2 Zwei weitere Grundlagenlabore der Informationstechnik, welche in (10b.1) nicht gewählt wurden (
0.0h KS / 4.0 ECTS)
- 700.107 Basic lab: Simulation technology and Matlab/Simulink (2.0h KS / 2.0 ECTS) Absolvierung im 3., 4., 5., 6. Semester empfohlen
-
10b.2 Zwei weitere Grundlagenlabore der Informationstechnik, welche in (10b.1) nicht gewählt wurden (
0.0h KS / 4.0 ECTS)
-
Fach: Informationstechnische Vertiefung sowie mathematische Ergänzung
(Wahlfach)
- Bachelorstudium Informationstechnik
(SKZ: 289, Version: 17W.1)
-
Fach: Grundlagenlabor Informationstechnik
(Wahlfach)
-
9a.1 Grundlagenlaborübungen der Informationstechnik (
0.0h KS / 12.0 ECTS)
- 700.107 Basic lab: Simulation technology and Matlab/Simulink (2.0h KS / 2.0 ECTS) Absolvierung im 4., 5., 6. Semester empfohlen
-
9a.1 Grundlagenlaborübungen der Informationstechnik (
0.0h KS / 12.0 ECTS)
-
Fach: Grundlagenlabor Informationstechnik
(Wahlfach)
- Bachelorstudium Informationstechnik
(SKZ: 289, Version: 17W.1)
-
Fach: Informationstechnische Vertiefung sowie mathematische Ergänzung
(Wahlfach)
-
10b.1 Wahl von 2 Laborübungen aus den angebotenen Grundlagenlaborübungen der Informationstechnik (
0.0h KS / 4.0 ECTS)
- 700.107 Basic lab: Simulation technology and Matlab/Simulink (2.0h KS / 2.0 ECTS) Absolvierung im 3. Semester empfohlen
-
10b.1 Wahl von 2 Laborübungen aus den angebotenen Grundlagenlaborübungen der Informationstechnik (
0.0h KS / 4.0 ECTS)
-
Fach: Informationstechnische Vertiefung sowie mathematische Ergänzung
(Wahlfach)
- Bachelorstudium Robotics and Artificial Intelligence
(SKZ: 295, Version: 22W.1)
-
Fach: Labs Robotics and AI
(Wahlfach)
-
7.1 Wahl von Laborübungen aus dem Angebot der Informationstechnik, sowie zu Robotics & AI (
0.0h KS / 12.0 ECTS)
- 700.107 Basic lab: Simulation technology and Matlab/Simulink (2.0h KS / 2.0 ECTS)
-
7.1 Wahl von Laborübungen aus dem Angebot der Informationstechnik, sowie zu Robotics & AI (
0.0h KS / 12.0 ECTS)
-
Fach: Labs Robotics and AI
(Wahlfach)
Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung
-
Sommersemester 2024
- 700.107 KS Basic lab: Simulation technology and Matlab/Simulink (2.0h / 2.0ECTS)
-
Sommersemester 2022
- 700.107 KS Grundlagenlabor: Simulationstechnik und Matlab/Simulink (2.0h / 2.0ECTS)
-
Sommersemester 2021
- 700.107 KS Grundlagenlabor: Simulationstechnik und Matlab/Simulink (2.0h / 2.0ECTS)
-
Sommersemester 2020
- 700.107 KS Grundlagenlabor: Simulationstechnik und Matlab/Simulink (2.0h / 2.0ECTS)
-
Sommersemester 2019
- 700.107 KS Grundlagenlabor: Simulationstechnik und Matlab/Simulink (2.0h / 2.0ECTS)
-
Sommersemester 2018
- 700.107 KS Grundlagenlabor: Simulationstechnik und Matlab/Simulink (2.0h / 2.0ECTS)
-
Sommersemester 2017
- 700.107 KS Grundlagenlabor: Simulationstechnik und Matlab/Simulink (2.0h / 2.0ECTS)
-
Sommersemester 2016
- 700.107 KS Grundlagenlabor: Simulationstechnik und Matlab/Simulink (2.0h / 2.0ECTS)
-
Sommersemester 2015
- 700.107 KU Grundlagenlabor: Simulationstechnik und Matlab/Simulink (2.0h / 2.0ECTS)
-
Sommersemester 2014
- 700.107 KU Grundlagenlabor: Simulationstechnik und Matlab/Simulink (2.0h / 2.0ECTS)
-
Sommersemester 2013
- 700.107 KU Grundlagenlabor: Simulationstechnik und Matlab/Simulink (2.0h / 2.0ECTS)