Intelligent Control (MECE525) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Intelligent Control MECE525 3 0 0 3 5
Pre-requisite Course(s)
MECE 306
Course Language English
Course Type N/A
Course Level Ph.D.
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Project Design/Management.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives This course introduces the basic theories and research areas of intelligent control; explains the knowledge representations, searching and reasoning mechanisms as the fundamental techniques of intelligent control.
Course Learning Outcomes The students who succeeded in this course;
  • Çeşitli akıllı denetim sistemlerinin, teorik prensiplerini ve yapılarını içermektedir. Akıllı denetim uygulamaları incelenmekte ve akıllı denetim alanındaki araştırma ve geliştirme eğilimleri aktarılmaktadır.
Course Content Intelligent control methodologies, learning control, fuzzy control, neurocontrol, neuro-fuzzy control.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Uncertainty in Model Simulations Uncertainty models and information representation: types of uncertainities and uncertainty measures. N/A
2 Intelligent control methodologies Analysis and comparison of intelligent control methods N/A
3 Learning Control. Modeling of Nonlinear Systems N/A
4 Fuzzy Control. Intelligent Control for Nonlinear Systems N/A
5 Knowledge-Based Multivariable Fuzzy Control. Model -Based Multivariable Fuzzy Control N/A
6 Neural Control N/A
7 Neuro-Fuzzy Control N/A
8 Project work N/A
9 Project work N/A
10 Project work N/A
11 Project work N/A
12 Project work N/A
13 Project work N/A
14 Project work N/A
15 Project work N/A
16 General Examination N/A

Sources

Course Book 1. Intelligent systems : modeling, optimization, and control. By Yung C. Shin and Chengying Xu. ISBN 978-1-4200-5176-6
Other Sources 2. Intelligent control: principles, techniques and applications. By Zi-Xing Cai. ISBN 981-02-2564-4

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation 1 30
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 30
Final Exam/Final Jury 1 40
Toplam 3 100
Percentage of Semester Work 60
Percentage of Final Work 40
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 carry out advanced research activities, both individual and as a member of a team
2 Ability to evaluate research topics and comment with scientific reasoning
3 Ability to initiate and create new methodologies, implement them on novel research areas and topics
4 Ability to produce experimental and/or analytical data in systematic manner, discuss and evaluate data to lead scintific conclusions
5 Ability to apply scientific philosophy on analysis, modelling and design of engineering systems
6 Ability to synthesis available knowledge on his/her domain to initiate, to carry, complete and present novel research at international level
7 Contribute scientific and technological advancements on engineering domain of his/her interest area
8 Contribute industrial and scientific advancements to improve the society through research activities

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class
Presentation/Seminar Prepration
Project
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury
Prepration of Final Exams/Final Jury
Total Workload 0