Course Syllabus
ECE 581 – Fuzzy Control
Department of Electrical & Computer Engineering
1. Course Number and Name:
2. Credit Units/Contact Hours:
3. Course Coordinator:
ECE 581 – Fuzzy Control
3/3
Ali Amini
4. Text, References & Software
Recommended Text:
Fuzzy Logic: Intelligence, Control, and Information. John Yen & Reza Langari, Prentice Hall
1999, ISBN 0-13-525817-0.
Additional References:
Fuzzy Engineering, Bart Kosko, Prentice Hall 1996, ISBN 0-13-124991-6.
Fuzzy Sets and Fuzzy Logic. Klir and Yuan, Prentice Hall 1995, ISBN 0-13-101171-5.
Software:
MATLAB: Control, Fuzzy Control and Simulink Tool Boxes, Math Works Inc.
Internet Resources:
http//hpme12.me.edu/matlab/html/
5. Specific Course Information
a. Course Description
This course consists of two parts. The first part introduces the basic concepts of fuzzy logic such
as fuzzy sets, rules, definitions, graphs, and properties related to fuzzification and defuzzification.
The second part of this course introduces fuzzy logic control and its application to control
engineering. This part discusses the basic fuzzy logic controllers, the relevant analytical issues,
and their roles in advanced hierarchical control systems.
b. Prerequisite by Topic
Students taking this course should have complete familiarity with the topics of Control System
(ECE 480) course. Specifically students should be familiar with linear system theory, continuous
as well as discrete. Understanding time domain (continuous and discrete), S-domain, Z-domain,
and frequency domain (continuous and discrete) in modeling, analyzing and solving linear
systems is the main prerequisite for taking this course. In order to understand fuzzy controllers a
comparison between these controllers and PID controllers is necessary. For this reason PID
controllers are discussed before beginning the discussion of fuzzy controllers. Although a
comparison of probability theory and fuzzy logic is made, the course of probability theory is not a
prerequisite. However the basic idea of probability is covered as part of this course.
c. Elective Course
6. Specific Goals for the Course
a. Specific Outcomes of Instructions – After completing this course the students should be able to:
1. Understand sets, operations, properties, and geometrical interpretations.
2. Understand linguistic variables and how they are used in relation to fuzzy problems.
3. Understand membership functions and have complete familiarity with different types
of membership functions as they are applied to fuzzy variables.
4. Convert a set of crisp inputs to fuzzy form using fuzzification techniques.
5. Understand fuzzy if then rules and use them for intelligent decision making.
6. Apply different methods of defuzzification to convert fuzzy outputs to crisp outputs.
7. Understand the differences between fuzzy logic and probability theory as applied to
engineering problems.
8. Understand fuzzy controllers and use them in systems with feedback.
9. Understand PID controllers and use them in systems with feedback.
10. Understand the differences between fuzzy controllers and PID controllers as well as
advantages and disadvantages of using one as opposed to the other.
11. Discuss fuzzy logic in hierarchical control.
12. Discuss fuzzy control in conjunction with stability theory.
b. Relationship to Student Outcomes
This supports the achievement of the following student outcomes:
a. An ability to apply knowledge of math, science, and engineering to the analysis of electrical
engineering problems.
b. An ability to design and conduct scientific and engineering experiments, as well as to analyze
and interpret data.
c. An ability to design systems which include hardware and/or software components within
realistic constraints such as cost, manufacturability, safety and environmental concerns.
d. An ability to function in multidisciplinary teams.
e. An ability to identify, formulate, and solve electrical engineering problems.
i. A recognition of the need for and an ability to engage in life-long learning.
k. An ability to use modern engineering techniques for analysis and design.
m. An ability to analyze and design complex devices and/or systems containing hardware and/or
software components.
n. Knowledge of math including differential equations, linear algebra, complex variables and
discrete math.
7. Topics Covered/Course Outline
1. Basic concepts of fuzzy logic.
2. Fuzzy relation, fuzzy graphs, and fuzzy arithmetic.
3. Fuzzy logic and probability theory.
4. Fuzzy logic in control engineering.
5. Hierarchical intelligent control.
6. Analytical issues in fuzzy logic control.
7. Fuzzy model identification.
Prepared by:
Ali Amini, Professor of Electrical and Computer Engineering, July 2012
Ali Amini, Professor of Electrical and Computer Engineering, March 2013