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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EEE 5109 SYSTEMS IDENTIFICATION ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR HATICE DOĞAN

Offered to

ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH) ELECTRICAL AND ELECTRONICS ENGINEERING NON -THESIS (EVENING PROGRAM) (ENGLISH) ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH) ELECTRICAL AND ELECTRONICS ENGINEERING (ENGLISH)

Course Objective

This course aims to teach the methods used to obtain a mathematical model of the system using input-output data and to validate the model of the identified system.

Learning Outcomes of the Course Unit

1   To be able to recognize a problem of system identification 2   To be able to use non-parametric system identification techniques 3   To be able to use parametric system identification techniques 4   To be able to identify a system using input-output data 5   To be able to validate the model of the identified system, and compare different models

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to System Identification 2 Mathematical Background 3 Nonparametric Identification I 4 Nonparametric Identification II 5 Nonparametric Identification III 6 Parametric Identification I 7 Parametric Identification II 8 Parametric Identification III 9 Parametric Identification IV 10 Validation Techniques I 11 Midterm Exam 12 Validation Techniques II 13 Practical applications of system identification 14 Practical applications of system identification

Recomended or Required Reading

Ljung, Lennart.System Identification: A Theory for the User. 2nd ed. Upper Saddle River, NJ: Prentice Hall, 1998. ISBN: 0136566952.

Planned Learning Activities and Teaching Methods

Lectures with active participation, classical midterm and final examinations, homeworks.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 ASG ASSIGNMENT 2 MTE MIDTERM EXAM 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE ASG * 0.30 + MTE * 0.30 + FIN * 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.30 + MTE * 0.30 + RST * 0.40 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Learning outcomes are evaluated by homeworks and examinations.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

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 Preparation for midterm exam 1 20 20 Preparation for final exam 1 24 24 Preparing assignments 5 10 50 Preparations before/after weekly lectures 14 4 56 Midterm 1 2 2 Final 1 2 2 TOTAL WORKLOAD (hours) 196

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 PO.14 PO.15 LO.1 1 LO.2 2 2 1 LO.3 2 2 1 LO.4 2 2 1 LO.5 2 2 1