COURSE UNIT TITLE

: FUZZY LOGIC COMPUTING AND CONTROL

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
MEC 5017 FUZZY LOGIC COMPUTING AND CONTROL ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

Offered to

Mechatronics Engineering
M.Sc. Mechatronics Engineering
Mechatronics Engineering

Course Objective

This graduate course in fuzzy-logic based computing and control system engineering aims to develop students understanding of how: (a) a fuzzy computing structure works and executes approximate reasoning algorithmencoded by fuzzy sets and relations; and (b) fuzzy- logic based computing is exploited to design fuzzy-logic control algorithms and control system engineering applications

Learning Outcomes of the Course Unit

1   to distunguish concept of fuzzy logic from crisp logic
2   to define arithmetic and logic operations usin fuuzy logic
3   to describe fuzzy model of an engineering system
4   to design fuzzy control system
5   to compare the effects of the different controller structures to the systems

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Basic concepts in Logic
2 Introduction to Fundamental Concepts of fuzzy logic
3 Fuzzy sets and Membership Functions
4 Fuzzy Relations, Fuzzy Operators and Arithmetic
5 Fuzzy Reasoning
6 Case Study: Fuzzyfication of Air Conditioning Problem
7 Midterm
8 Fundamentals of Control Design
9 Fuzzy Logic Control
10 Case study: Design of an Mandani Type Fuzzy Controller
11 Case study: Design of a Takagi Sugeno Type Controller
12 Fuzzy Supervisory Control
13 Case Study: Fuzzy Integrated PID Control
14 Case Study: Fuzzy logic control applications in Mechatronic systems

Recomended or Required Reading

TEXTBOOK:
John YEN & Reza LANGARI, Fuzzy Logic Intelligence, Control and Information-
REFERENCE BOOKS:
Fuzzy Logic with Engineering Applications, by Timothy J. Ross, 2004
Introduction to Fuzzy Logic using MATLAB, S N Sivanandam

Planned Learning Activities and Teaching Methods

PowerPoint presentations, home works, computer applications

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG 1 ASSIGNMENT 1
2 ASG 2 ASSIGNMENT 2
3 MTE MIDTERM EXAM
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE ASG 1 * 0.10 + ASG 2 * 0.10 + MTE * 0.20 + FIN *0.60
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) ASG 1 * 0.10 + ASG 2 * 0.10 + MTE * 0.20 + RST *0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

levent.cetin@deu.edu.tr

Office Hours

Friday 15:00-17:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 13 3 39
Preparing assignments 2 28 56
Preparation for final exam 1 30 30
Preparation for midterm exam 1 20 20
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 190

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15
LO.1422
LO.24332
LO.33434
LO.434343
LO.54444233