COURSE UNIT TITLE

: CONTROL SYSTEMS MODELING AND SIMULATIONS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EED 4303 CONTROL SYSTEMS MODELING AND SIMULATIONS ELECTIVE 3 2 0 6

Offered By

Electrical and Electronics Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR HATICE DOĞAN

Offered to

Electrical and Electronics Engineering

Course Objective

The aim of this course is to teach the control system modelling by using both computer simulation and mathematical techniques.

Learning Outcomes of the Course Unit

1   Be able to identify the fundamentals of modeling and simulation of the control systems.
2   Be able to derive the mathematical models of the control system plants.
3   Be able to apply system identification techniques
4   Be able to predict the dynamic behaviour of the control systems
5   Be able to use MATLAB and simulink software for the control system modelling and simulations
6   Be able to validate the models and report the results

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

EED 3006 - CONTROL SYSTEMS
EED 3016 - CONTROL SYSTEMS

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to modeling and simulation
2 Differential Equations Introduction to Simulink
3 Modelling I: White Box Modelling Modelling of Mechanical Systems
4 Modelling I: White Box Modelling Modelling of Electrical Systems
5 Linearization of Nonlinear Systems White box modelling examples
6 Modelling II: System Identification Non-parametric Methods I
7 Modelling II: System Identification Non-parametric Methods II
8 Modelling II: System Identification Parameteric System Identification I
9 Modelling II: System Identification Parameteric System Identification II
10 Modelling II: System Identification Parameter Estimation Methods, Static Systems Static Systems
11 Modelling II: System Identification Parameter Estimation Methods, Dynamic Systems I Dynamic Systems
12 Modelling II: System Identification Parameter Estimation Methods , Dynamic Systems II Dynamic Systems II
13 Model Validation Techniques
14 Developing Models from Experimental Data using System Identification MATLAB Toolbox

Recomended or Required Reading

-System Identification: An Introduction, Karel J. Keesman, Springer-Verlag 2011.
-System Identification - Theory For the User, L. Ljung, PTR Prentice Hall, 1999
-SIMULINK Dynamic System Simulation for MATLAB, Mathworks, 2011.

Resources:
-Mathematical Modeling and Simulation: Introduction for Scientists and Engineers, Kai Velten , Wiley-VCH,2009.
-Modeling and simulation of dynamic systems, R. L., and Lawrence, K. L. Prentice-Hall, 1997.
-Modeling and Simulation for Automatic Control, Olav Egeland and Jan Tommy Gravdahl, 2002, Marinecybernetics.
-Simulation of Dynamic Systems with MATLAB and Simulink, Klee, H.,CRC Press, 2007.

Planned Learning Activities and Teaching Methods

A series of lectures on course materials will be given using PowerPoint presentations. To support course materials, laboratory studies will be done.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 LAB LABORATORY
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + LAB * 0.20 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + LAB * 0.20 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Learning outcomes will evaluated by examinations and laboratory works.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Asst. Prof. Dr. Hatice Doğan
e-mail:hatice.dogan@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Labratory 14 2 28
Preparation for midterm exam 1 6 6
Preparation for final exam 1 8 8
Lab Preparation 14 3 42
Preparations before/after weekly lectures 14 2 28
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 158

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13
LO.155
LO.255
LO.3553
LO.453
LO.545
LO.64533