htw saar QR-encoded URL
Back to Main Page Choose Module Version:
emphasize objectives XML-Code


Automation Engineering

Module name (EN):
Name of module in study programme. It should be precise and clear.
Automation Engineering
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Industrial Engineering, Bachelor, ASPO 01.10.2013
Module code: WIBASc-515
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
2V+2PA (4 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
Semester: 5
Mandatory course: yes
Language of instruction:
Written exam

[updated 02.07.2019]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

WIBASc-515 Industrial Engineering, Bachelor, ASPO 01.10.2013 , semester 5, mandatory course
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
60 class hours (= 45 clock hours) over a 15-week period.
The total student study time is 150 hours (equivalent to 5 ECTS credits).
There are therefore 105 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
WIBASc145 Physics
WIBASc165 Mathematics I
WIBASc245 Manufacturing Engineering
WIBASc255 Statistics
WIBASc265 Mathematics II
WIBASc345 Design Technology / CAD
WIBASc355 Computer Science / Programming
WIBASc445 Electrical Engineering

[updated 31.12.2019]
Recommended as prerequisite for:

[updated 31.01.2020]
Module coordinator:
Prof. Dr. Frank Kneip
Prof. Dr. Frank Kneip

[updated 31.12.2019]
Learning outcomes:
After successfully completing this module students will:
_        have learned the basics of control engineering for linear, time-invariant control systems.
_        can describe and characterize suitable systems by combining basic transfer functions.
_        have the ability to evaluate a given linear and time-invariant system in terms of stability.
_        be able to select a known controller type for a given system and justify their choice, and
_        be able to apply a tuning procedure for the selected controller and parameterize the controller.
_        be familiar with saturation of control variables and their effects, as well as have insight into the subject of nonlinear systems, feedforward control and iterative learning controllers.
_        have the ability to apply what they have learned in the Matlab/Simulink simulation environment and in connection with Lego Mindstorms NXT and Labview for predefined systems.

[updated 02.07.2019]
Module content:
1. Principles of feedforward and feedback control
-        Basic principle feedforward and feedback control
-        Controllers, controlled systems, sensor and actuator technology
-        Areas of application and requirements
2. System description and stability
-        Linear time-invariant systems
-        Description in the time domain
-        Description in the frequency domain
-        Basic transfer functions
-        Parallel and series connection of transfer functions
-        Step response
-        Frequency response, root locus, Bode plot
-        Stability of linear systems
3. Types of controllers
-        Basic types of controllers: P-, I-, PI-, PD-, PID controllers
-        Characteristics and areas of application of different types of controllers
4. Controller design
-        Objectives of a controller strategy
-        Tuning rules:
-  Tuning according to Ziegler and Nichols
-  Tuning according to Chien, Hrones and Reswick
-  Tuning according to the T-Sum Rule
-        Pole placement
-        Dimensioning with Bode plots
5. Further topics:
- Saturation of control variables, anti-wind-up
- Disturbances and tolerances
- Nonlinear systems
- Feedforward (control)
- Iterative learning controllers
Experiments and simulations:
-        Simulation-supported tests in Matlab/Simulink
-        Lab experiments with Lego Mindstorms NXT and Labview

[updated 02.07.2019]
Teaching methods/Media:
Lecture with integrated exercises and experiments, presentation, lecture notes, blackboard, PC, Matlab/Simulink, Labview, Lego Mindstorms NXT

[updated 02.07.2019]
Recommended or required reading:
_        Lunze, J.: Regelungstechnik 1; 9. Auflage, Springer Verlag, 2013
_        Unbehauen, H.: Regelungstechnik 1; 15. Auflage, Vieweg+Teubner Verlag, 2008
_        Reuter, M., Zacher, S.: Regelungstechnik für Ingenieure; 12. Auflage, Vieweg+Teubner Verlag, 2008
_        Tröster, F.: Steuerungs- und Regelungstechnik für Ingenieure; 3. Auflage, Oldenbourg Verlag, 2011
_        Roddeck, W.: Einführung in die Mechatronik; 4. Auflage,  Vieweg+Teubner Verlag, 2012
_        Bode, H.: Systeme der Regelungstechnik mit Matlab und Simulink _ Analyse und Simulation; Oldenbourg Verlag, 2010
_        Gasperi, M.: Labview for Lego Mindstorms NXT; National Technology & Science Press, 2008
_        RRZN Handbuch: Matlab/Simulink; 4. Auflage, 2012

[updated 02.07.2019]
[Wed Jul 24 10:13:52 CEST 2024, CKEY=wwxa, BKEY=wi2, CID=WIBASc-515, LANGUAGE=en, DATE=24.07.2024]