700.107 (24S) Basic lab: Simulation technology and Matlab/Simulink

Sommersemester 2024

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Erster Termin der LV
08.03.2024 11:45 - 13:15 B04.1.02 On Campus
Nächster Termin:
19.04.2024 11:45 - 13:15 B04.1.02 On Campus

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 20 (20 max.)
Organisationseinheit
Unterrichtssprache Englisch
LV-Beginn 08.03.2024
eLearning zum Moodle-Kurs

Zeit und Ort

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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. 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 ODE-solvers in 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. Oscillatory systems in engineering: Simulation of complex system- models using MATLAB/SIMULINK

Chapter 6. Traffic flow analysis: Simulation of coupled ODEs and PDEs used for traffic flow modeling in transportation engineering.

Chapter 7. Signal processing: MATLAB codes for the extraction of signals embedded in noise.

Erwartete Vorkenntnisse

-

Curriculare Anmeldevoraussetzungen

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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

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Prüfungsmethode/n

• The final exam takes place on-campus in the form of a written exam.

• The total duration of the final exam is 3 to 4 hours. 

Prüfungsinhalt/e

All chapters of the lecture

(The final exam takes into account all chapters of the lecture.)

Beurteilungskriterien/-maßstäbe

The following four possibilities/options are offered as evaluation criteria: A student must choose one of the options below

Option 1. * Final Exam (95 /%) + BONUS 1 (5 /%).

• BONUS 1. Participation in the course (i.e. attending the course/lecture, asking questions, answering questions, etc.) (5% of the total mark (or total grade) of the final Exam).


Option 2. * Final Exam (95 /%) + BONUS 2 (5 /%).

• BONUS 2. homework (5% of the total mark (or total grade) of the final Exam).

 

Option 3. * Final Exam (90 /%) + BONUS 1 (5 /%) + BONUS 2 (5 /%). 

This option is offered to a student who has chosen BONUS 1 and BONUS 2.


Option 4. * Final Exam without BONUS (100 % of the total mark (or total grade) of the final Exam).

This option is offered to a student who has chosen neither BONUS 1 nor BONUS 2.

Beurteilungsschema

Note Benotungsschema

Position im Curriculum

  • Bachelorstudium Angewandte Informatik (SKZ: 511, Version: 19W.2)
    • Fach: Informationstechnik und Robotik (Wahlfach)
      • 8.3 Informationstechnik und Robotik ( 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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)

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

Sommersemester 2023
  • 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)