ECTS - Introduction to Systems Analysis
Introduction to Systems Analysis (EE504) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Introduction to Systems Analysis | EE504 | 3 | 0 | 0 | 3 | 5 |
| Pre-requisite Course(s) |
|---|
| None. However, a prior differential equations, signals and systems and/or a circuit theory course is recommended |
| Course Language | English |
|---|---|
| Course Type | N/A |
| Course Level | Natural & Applied Sciences Master's Degree |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Discussion, Question and Answer, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | Teaching the graduate students of basic concepts such as basic linear algebra, linear system representations, analysis in Laplace, Z, Fourier and State-Space domains, transformation between continuous and discrete time systems. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Review of linear algebra concepts, classifications of systems and system representations, continuous and discrete time systems, state space realizations, analysis techniques: frequency domain, Laplace and z-domain analyses, solutions of linear systems, stability analysis; assessment of the techniques by a computational tool such as MATLAB. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Elementary matrix theory, Matrix addition and multiplication, Matrix and Vector multiplication, Properties of linear equations | Review last week and Glance this week’s topics from the lecture |
| 2 | Vectors, Vector spaces, Linear dependence and independence, Basis concept, Linear spans, Normed vector spaces | Glance this week’s topics from the lecture |
| 3 | Null and Range spaces of matrices, Eigenvalues, Eigenvectors, Diagonalization | Review last week and Glance this week’s topics from the lecture |
| 4 | Singular Value Decomposition | Glance the last weeks topics |
| 5 | MATLAB Session: Vectors and Matrices in MATLAB | Review last week and Glance this week’s topics from the lecture |
| 6 | Introduction to Fourier, Laplace and Z-Transforms | Review last week and Glance this week’s topics from the lecture |
| 7 | Continuous and Discrete Time systems, Transfer function representations | Review last week and Glance this week’s topics from the lecture |
| 8 | MIDTERM-I (1 Hour MATLAB Exam+2 Hour Theoretical) | Review last week and Glance this week’s topics from the lecture |
| 9 | Representation of linear systems in state space and transformation between transfer function and state space representations. | Review last week and Glance this week’s topics from the lecture |
| 10 | Solutions of linear systems | Review last week and Glance this week’s topics from the lecture |
| 11 | Analysis in Fourier Domain (Frequency response) | Review last week and Glance this week’s topics from the lecture |
| 12 | Analysis in Fourier Domain (Frequency response) | Review last week and Glance this week’s topics from the lecture |
| 13 | Connections to nonlinear systems, linearization and local stability | Review last week and Glance this week’s topics from the lecture |
| 14 | Transformation between continuous and discrete time systems (s-to-z) | Review last week and Glance this week’s topics from the lecture |
| 15 | The transformation between continuous and discrete time systems in state space. | Review the last week's topics |
| 16 | MIDTERM-II (1 Hour MATLAB Exam+2 Hour Theoretical) | Review last week and Glance this week’s topics from the lecture |
Sources
| Course Book | 1. Oppenheim, A. V., & Willsky, A. S. (1997). with SH Nawab, Signals and Systems. Prentice—Hall,, 1, 997. |
|---|---|
| 2. Ogata, K. (1997). Modern Control Engineering (3rd Ed.). Prentice-Hall, Inc., Upper Saddle River, NJ, USA. | |
| 3. Ogata, K. (1995). Discrete-time control systems (Vol. 2). Englewood Cliffs, NJ: Prentice Hall. | |
| 4. Kuo, B. C. (1981). Automatic control systems. (8th ed.). John Wiley & Sons, Inc., New York, NY, USA. | |
| 5. Lipschutz, S., & Lipson, M. (2000). Schaum's Outline of Linear Algebra. McGraw Hill Professional. | |
| Other Sources | 6. Notes to be distributed by the instructor(s) of the course in class. |
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | - | - |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 2 | 50 |
| Final Exam/Final Jury | 1 | 35 |
| Toplam | 3 | 85 |
| Percentage of Semester Work | 65 |
|---|---|
| Percentage of Final Work | 35 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Ability to expand and get in-depth information with scientific researches in the field of mechanical engineering, evaluate information, review and implement. | |||||
| 2 | Have comprehensive knowledge about current techniques and methods and their limitations in Mechanical engineering. | |||||
| 3 | To complete and apply knowledge by using scientific methods using uncertain, limited or incomplete data; use information from different disciplines. | |||||
| 4 | Being aware of the new and developing practices of Mechanical Engineering and being able to examine and learn when needed. | |||||
| 5 | Ability to define and formulate problems related to Mechanical Engineering and develop methods for solving and apply innovative methods in solutions. | |||||
| 6 | Ability to develop new and/or original ideas and methods; design complex systems or processes and develop innovative/alternative solutions in the designs. | |||||
| 7 | Ability to design and apply theoretical, experimental and modeling based researches; analyze and solve complex problems encountered in this process. | |||||
| 8 | Work effectively in disciplinary and multi-disciplinary teams, lead leadership in such teams and develop solution approaches in complex situations; work independently and take responsibility. | |||||
| 9 | To establish oral and written communication by using a foreign language at least at the level of European Language Portfolio B2 General Level. | |||||
| 10 | Ability to convey the process and results of their studies systematically and clearly in written and oral form in national and international environments. | |||||
| 11 | To know the social, environmental, health, security, law dimensions, project management and business life applications of engineering applications and to be aware of the constraints of their engineering applications. | |||||
| 12 | Ability to observe social, scientific and ethical values in the stages of data collection, interpretation and announcement and in all professional activities. | |||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 14 | 3 | 42 |
| Presentation/Seminar Prepration | |||
| Project | |||
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 2 | 10 | 20 |
| Prepration of Final Exams/Final Jury | 1 | 20 | 20 |
| Total Workload | 130 | ||