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)
MECE306
Course Language English
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 Coordinator
Course Lecturer(s)
Course Assistants
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;
  • To learn z- and inverse-z transform
  • To be able to model and analyse discrete time control systems
  • To understand and practice design and realization of discrete controllers
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
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.
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
Percentage of Final Work 30
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 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
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