At the end of this course, the students; 1) Ability An ability to apply knowledge of mathematics, science, and engineering. 2) An ability to design and conduct experiments, as well as to analyze and interpret data. 3) 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. 4) An ability to identify, formulate, and solve engineering problems. 5) An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
None
COURSE DEFINITION
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
1st Week
Models for systems and signals
2nd Week
Basic testing and identification methods
3rd Week
Basic concepts of linear system theory, probability and stochastic processes.
4th Week
Basic concepts of linear system theory, probability and stochastic processes.
5th Week
Basic concepts of linear system theory, probability and stochastic processes.
6th Week
Fourier analysis of signals
7th Week
Least squares estimation.
8th Week
MIDTERM
9th Week
Identification of transfer function models by parametric methods
10th Week
Identification of transfer function models by parametric methods
11th Week
Identification of transfer function models by parametric methods
12th Week
Spectral estimation.
13th Week
Spectral estimation.
14th Week
Design samples
RECOMENDED 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
1
10
Quiz
2
5
Project
1
10
Total(%)
60
Contribution of In-term Studies to Overall Grade(%)
60
Contribution of Final Examination to Overall Grade(%)
40
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
2
2
Preparation for Quiz
2
5
10
Individual or group work
14
6
84
Preparation for Final exam
1
70
70
Course hours
14
3
42
Preparation for Midterm exam
1
50
50
Laboratory (including preparation)
Final exam
1
2
2
Homework
Project
1
50
50
Quiz
2
2
4
Total Workload
314
Total Workload / 30
10,46
ECTS Credits of the Course
10
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)