ECTS - Digital Control
Digital Control (MECE406) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
---|---|---|---|---|---|---|---|
Digital Control | MECE406 | Area Elective | 3 | 0 | 0 | 3 | 5 |
Pre-requisite Course(s) |
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MECE306 |
Course Language | English |
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Course Type | Elective Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Question and Answer, Problem Solving, Team/Group. |
Course Lecturer(s) |
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Course Objectives | This course aims to introduce design and implementation of control systems which are based on the use of computers. The course describes issues that are related to discrete time and their relevance to continuous time. Students equipped with knowledge on designing continuous time control systems will study discretization of systems and controllers, implementation of closed-loop control, analysis and interpretation of results. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Z-transform, discretization, stability analysis, steady state analysis, root locus, design in discrete time, state space and structural properties of discrete time systems, Lyapunov theory and observer based design. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Introduction, Nyquist Sampling Theorem | NA |
2 | Z transform, inverse Z transform, convolution property, initial and final value theorem | NA |
3 | Types of difference equations, (MA, AR, ARMA, ARMAX), approximation methods for obtaining G(z) from G(s), FR, BR, TR, PZ mapping, ZOH equivalence, step invariance, impulse response discretization, discretization by solution of the state equations, pade approximation, mapping from s-domain to z-domain, finding Z transform from block diagrams, prewarping (matching of half power frequency) | NA |
4 | Stability analysis, jury test, routh criterion with bilinear transformation | NA |
5 | Realizations: direct, series, parallel, ladder | NA |
6 | Steady state error analysis | NA |
7 | Root locus, design based on root locus | NA |
8 | Direct design method of Raggazzini, discrete PID | NA |
9 | Discrete time state space representation of dynamical systems, structural properties; controllability, observability, stabilizability, detectability | NA |
10 | Lyapunov stability for discrete time systems | NA |
11 | Pole placement, Bass-Gura formula, Ackermann formula | NA |
12 | Discrete time observers | NA |
13 | Problem session | NA |
14 | Problem session | NA |
15 | Problem session | N/A |
16 | Final Examination | N/A |
Sources
Course Book | 1. Digital Control, K. Moudgalya, ISBN: 978-0470031445, Wiley, 2007. |
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Other Sources | 2. 1. Digital Control System Analysis and Design, C. L. Phillips, H. T. Nagle, |
3. Discrete-Time Control Systems, K. Ogata, ISBN: 0-13-328642-8, Pearson, 1995. |
Evaluation System
Requirements | Number | Percentage of Grade |
---|---|---|
Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | 5 | 10 |
Presentation | - | - |
Project | 1 | 20 |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 2 | 40 |
Final Exam/Final Jury | 1 | 30 |
Toplam | 9 | 100 |
Percentage of Semester Work | 70 |
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Percentage of Final Work | 30 |
Total | 100 |
Course Category
Core Courses | X |
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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 | Adequate knowledge of subjects related to mathematics, natural sciences, and Electrical and Electronics Engineering discipline; ability to apply theoretical and applied knowledge in those fields to the solution of complex engineering problems. | X | ||||
2 | An ability to identify, formulate, and solve complex engineering problems, ability to choose and apply appropriate models and analysis methods for this. | X | ||||
3 | An ability to design a system, component, or process under realistic constraints to meet desired needs, and ability to apply modern design approaches for this. | X | ||||
4 | The ability to select and use the necessary modern techniques and tools for the analysis and solution of complex problems encountered in engineering applications; the ability to use information technologies effectively | |||||
5 | Ability to design and conduct experiments, collect data, analyze and interpret results for investigating complex engineering problems or discipline-specific research topics. | |||||
6 | An ability to function on multi-disciplinary teams, and ability of individual working. | |||||
7 | Ability to communicate effectively orally and in writing; knowledge of at least one foreign language; active report writing and understanding written reports, preparing design and production reports, the ability to make effective presentation the ability to give and receive clear and understandable instructions. | |||||
8 | Awareness of the necessity of lifelong learning; the ability to access knowledge, follow the developments in science and technology and continuously stay updated. | |||||
9 | Acting compliant with ethical principles, professional and ethical responsibility, and knowledge of standards used in engineering applications. | |||||
10 | Knowledge about professional activities in business, such as project management, risk management, and change management awareness of entrepreneurship and innovation; knowledge about sustainable development. | |||||
11 | Knowledge about the impacts of engineering practices in universal and societal dimensions on health, environment, and safety. the problems of the current age reflected in the field of engineering; awareness of the legal consequences of engineering solutions. |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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Course Hours (Including Exam Week: 16 x Total Hours) | 14 | 2 | 28 |
Laboratory | |||
Application | |||
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 14 | 2 | 28 |
Presentation/Seminar Prepration | |||
Project | 1 | 20 | 20 |
Report | |||
Homework Assignments | 6 | 4 | 24 |
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 2 | 15 | 30 |
Prepration of Final Exams/Final Jury | 1 | 20 | 20 |
Total Workload | 150 |