COURSE DESCRIPTION AND APPLICATION INFORMATION

Course Name Code Semester T+A+L (hour/week) Type (C / O) Local Credit ECTS
Fuzzy Logic Control MTE 422 Fall 03+00+00 Elective 3 6
Academic Unit: Department of Mechatronics Engineering
Mode of Delivery: Face to face
Prerequisites: None
Language of Instruction: English
Level of Course Unit: Undergraduate
Course Coordinator: - -
Course Objectives: The objective of this course is to introduce the main principles of analysis and design methods of intelligent control systems. The students are introduced to the design and analysis of intelligent control systems using Fuzzy Logic. In the design process, computer-based software is explained to the students. (MATLAB Fuzzy Logic Toolbox)
Course Contents: -
Learning Outcomes of the Course Unit (LO):
  • 1- Understandıng the general ideas about fuzzy sets, fuzzy operations, fuzzy relations and membership functions.
  • 2- Understanding the principles of fuzzy systems and construction of rule-based fuzzy systems.
  • 3- Apply intelligent techniques to complex engineering problems, including control systems.
  • 4- Mathematical representation of fuzzy systems.
  • 5- Distinguish between classical and intelligent control methods
  • 6- Employing computer aided software in the analysis and design of intelligent control systems.
  • 7- Basic approaches to the design of the fuzzy controller, including the use of proportional, integral, and derivative terms.
Planned Learning Activities and Teaching Methods: -


WEEKLY SUBJECTS AND RELATED PREPARATIONS

WeekSubjectsRelated Preperation
1 Introduction to conventional and intelligent control systems Modern Control Systems By Ogata
2 Fuzzy sets, membership functions, and the Rule-Base
3 Operations on fuzzy sets
4 The Inference mechanism and decision making
5 Mamdani fuzzy systems
6 Takagi-Sugeno fuzzy systems
7 Introduction to fuzzy Logic Toolbox MATLAB Mathworks Fuzzy Logic Toolbox Tutorial
8 Introductıon to Fuzzy control
9 Design examples and case studies (Motor Control- Cruise Control etc )
10 Formulation of Fuzzy control systems
11 Tuning the fuzzy PID controllers and Membership functions
12 Design examples and case studies (Inverted Pendulum 1)
13 Design examples and case studies (Inverted Pendulum 2)
14 Students presentations


REQUIRED AND RECOMMENDED READING

Fuzzy Control First Edition
by Kevin M. Passino (Author), Stephan Yurkovich (Author)


OTHER COURSE RESOURCES

Journal and conference papers – Lecture notes - Mathworks Fuzzy Logic Toolbox Tutorial


ASSESSMENT METHODS AND CRITERIA

Semester RequirementsNumberPercentage of Grade (%)
Project 1 20
Homework Assignments 1 20
Presentation / Jury 1 20
Midterms / Oral Exams / Quizes 1 20
Final Exam 1 20
Total: 5 100


WORKLOAD

EventsCountDuration (Hours)Total Workload (hour)
Course Hours14342
Project24896
Homework Assigments326
Preparation for Presentation / Jury236
Total Workload (hour):150


THE RELATIONSHIP BETWEEN COURSE LEARNING OUTCOMES (LO) AND PROGRAM QUALIFICATIONS (PQ)

# PQ1 PQ2 PQ3 PQ4 PQ5 PQ6 PQ7 PQ8 PQ9 PQ10
LO1                    
LO2                    
LO3                    
LO4                    
LO5                    
LO6                    
LO7