1. بسم الله الرحمن الرحيم Islamic University of Gaza Electrical Engineering Department

2. Fuzzy Logic Control EELE 6306By
Basil Hamed, Ph. D.
Control Systems Engineering

3. Course Syllabus Islamic University of Gaza Faculty of Engineering
Department of Electrical and Computer Engineering
Fuzzy Logic Control EELE 6321
Prerequisite: EELE 3360 or consent of instructor
Instructor : Basil Hamed, Ph.D. Control Systems Engineering
Office : B329
iugaza.edu
WebSite : : Ext. 2875
Meeting :Monday 2:00-5:00 (I 614)

4. Course Syllabus Course Description:
Fuzzy logic is a design method that can be effectively applied to problems that, because of complex, nonlinear or ambiguous system models, cannot be easily solved using traditional analytical control techniques.  This course discusses the types of applications for which fuzzy control is useful and introduces basic concepts of fuzzy set theory, fuzzy logic operations, fuzzification and de-fuzzification. Several types of fuzzy control design.

5. Course Syllabus
Text Book: Fuzzy Logic with Engineering Applications, 3rd Ed. John-Wiley, 2004, T.J. Ross,
References:
L. X. Wang, "A Course in Fuzzy Systems and Control", Prentice-Hall, 1997.
K. M. Passino, "Fuzzy Control", Addison-Wesley, 1998.
Fuzzy Set Teory, 1997, G.Klir et al. Prentice Hall
Fuzzy Sets and Fuzzy Logic 1995, G Klir et al. Prentice Hall
Foundation of Fuzzy Control ,Jan Jantzen 2007

6. Course Objectives The objectives of this course are to:
Help students to be familiar with the fundamental concepts of fuzzy set theory and fuzzy logic;
Foster competence in recognizing the feasibility and applicability of the design and implementation of intelligent systems (that employ fuzzy logic) for specific application areas; and
Help students develop a sufficient understanding of fuzzy system design methodology and how it impacts system design and performance

7. Materials Covered: 1- Introduction, Definitions and Concepts
Intelligent Control
Fuzzy Logic
Fuzzy Control
Applications
Rule Base
Fuzzy Sets
Classic versus Fuzzy Control System Design
An Example of Fuzzy Control
2-       Fuzzy Mathematics
Fuzzy Sets and Membership Functions
Mathematical Operations on Fuzzy Sets
Fuzzy Relations
Linguistic Variables
Fuzzy Rules
Approximate Reasoning

8. Materials Covered: 3- Fuzzy Systems Fuzzy Rule Base
Fuzzy Inference Engine
Fuzzification
Defuzzification
Mathematical Representations of Fuzzy Systems
The Approximation Properties of Fuzzy Systems
4-       Design of Fuzzy Controllers
Trial and Error Approach
Control surface of a fuzzy controller
Stable Fuzzy Controllers
Fuzzy Supervisory Control
Fuzzy Gain Scheduling
TSK Fuzzy Systems

9. Course Intended Learning Outcomes:
Upon successful completion of the course, students should be able to:
Utilize the state of the art topics of fuzzy control in their research activities.
Design fuzzy systems and fuzzy controllers. exhibit familiarity with the fundamental concepts of fuzzy set theory and fuzzy logic;
Recognize the feasibility and applicability of the design and implementation of intelligent systems (that employ fuzzy logic) for specific application areas; and
Understand fuzzy system design methodology and how it impacts system design and performance.

10. Course Syllabus Grading System: Homework 10 %
Project & Presentation %
Mid term Exam (Paper) 20 % ( 6/11/ 2017 )
Final Exam % ( 25/12/ 2017 )
Office Hours::
Saturday, Monday, Wednesday (11:00-1:00)
Sunday (9:00-11:00)
Open-door policy, by appointment or as posted.

11. Homework
There will be several homework assignments/computer projects during the term. These assignments will require students to program in MATLAB or a similar language. Students can seek help and work together on homework and projects, but each student must turn in his/her own write-up. 

12. Projects
Students will be required to develop an application of fuzzy logic to a problem of their choice. They will prepare a paper, including a survey of current literature, and make a presentation to the class.  Students are encouraged to use material related to their research activities.  Projects must be approved by the instructor.  

13. Computer Usage
Extensive use of MATLAB or LabVIEW for computer aided analysis and simulation. Students are required to use these tools and equipment for special project and homework development.

14. Signals
LTI
System +
H(z)
G(z)

15. What is a Control System
A Process that needs to be controlled:
To achieve a desired output
By regulating inputs
A Controller: a mechanism, circuit or algorithm
Provides required input
For a desired output
Desired
Output
Required
Input
Process
Output
Controller

16. What is a System?
System: Block box that takes input signal(s) and converts to output signal(s).
Continuous-Time System:
System
Input
Output

17. Closed Loop Control Open-loop control is ‘blind’ to actual output
Closed-loop control takes account of actual output and compares this to desired output
Measurement
Desired
Output + -
Process
Dynamics
Controller/
Amplifier
Output
Input

18. Model of Control System
Desired System
Performance
Control
Noise
Signal Capture
Actuators
Sensors
Mechanical
System
Disturbances
Environment

19. Digital Control System
Configuration

21. Control Control: Mapping sensor readings to actuators
Essentially a reactive system
Traditionally, controllers utilize plant model
A model of the system to be controlled
Given in differential equations
Control theory has proven methods using such models
Can show optimality, stability, etc.
Common term: PID (proportional-integral-derivative) control

22. Fuzzy Control When plant model unavailable
A set of rules associating sensor readings with action
IF Close-by(right-sensor) THEN Left
IF Clear(forward-sensor) THEN Forward
IF Right(goal-location) THEN Right
All rules fire in parallel, and their results are combined

23. Fuzzy Logic Fuzzy logic:
A way to represent variation or imprecision in logic
A way to make use of natural language in logic
Approximate reasoning
Humans say things like "If it is sunny and warm today, I will drive fast"
Linguistic variables:
Temp: {freezing, cool, warm, hot}
Cloud Cover: {overcast, partly cloudy, sunny}
Speed: {slow, fast}

24. Fuzzy Controller

25. See You next Monday