SYSTEM MODELING AND IDENTIFICATION

MAK612

Course Code: MAK612
Semester: -
Theory+Practice: 3 + 0
ECTS: 10

Course Type

Elective Course

Course Level

Doctorate Of Science

Year of Study

Semester

ECTS

Name of Lecturer(s)

Learning Outcomes

At the end of this course, the students;

Ability An ability to apply knowledge of mathematics, science, and engineering.
An ability to design and conduct experiments, as well as to analyze and interpret data.
An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability.
An ability to identify, formulate, and solve engineering problems.
An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

None

Course Description

ling of complex systems, Lagrange equations. Bond diagrams. System identification, estimation of transient response, spectrum and frequency functions. Least squares estimation. Parametric identification of dynamic systems. Validation of models.

Course Contents

WEEK	TOPICS
1^st Week	Models for systems and signals
2^nd Week	Basic testing and identification methods
3^rd Week	Basic concepts of linear system theory, probability and stochastic processes.
4^th Week	Basic concepts of linear system theory, probability and stochastic processes.
5^th Week	Basic concepts of linear system theory, probability and stochastic processes.
6^th Week	Fourier analysis of signals
7^th Week	Least squares estimation.
8^th Week	MIDTERM
9^th Week	Identification of transfer function models by parametric methods
10^th Week	Identification of transfer function models by parametric methods
11^th Week	Identification of transfer function models by parametric methods
12^th Week	Spectral estimation.
13^th Week	Spectral estimation.
14^th Week	Design samples

Recommended or Required Reading

Modeling Identification and Simulation of Dynamic Systems P.P.J. van den Bosch, A.C. van der Klauw, CRC Press 1994
Modeling of Dynamic Systems L. Ljung and T. Glad Prentice Hall 1994
System Modeling and Identification R.Johanessen Prentice Hall 1993
L. Ljung: System Identification: Theory for the User. Prentice Hall 1999, 2nd ed.

Planned Learning Activities and Teaching Methods

Lecture

Assessment Methods and Criteria

	Quantity	Percentage (%)
Mid-term	1	35
Assignment	5	20
Total(%)		55
Contribution of In-term Studies to Overall Grade(%)		55
Contribution of Final Examination to Overall Grade(%)		45
Total(%)		100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Midterm exam	1	3	3
Preparation for Quiz
Individual or group work	14	3	42
Preparation for Final exam	1	50	50
Course hours	14	3	42
Preparation for Midterm exam	1	30	30
Laboratory (including preparation)
Final exam	1	3	3
Homework	5	25	125
Total Work Load			295
Total Work Load / 30 (h)			9.83
ECTS Credit of the Course			10

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4	LO5
K1	X
K2		X
K3			X
K4
K5				X
K6
K7
K8
K9
K10
K11					X