Cleveland State University

Department of Electrical and Computer Engineering

 

EEC 645/745, ESC 794

Intelligent Control Systems

Syllabus, Fall 2010

 

Instructor:               

Dan Simon

Telephone: 216-687-2589

E-mail: d.j.simon@csuohio.edu

Web: http://academic.csuohio.edu/simond/courses/eec645

                                   

Prerequisites:         

EEC 440 (Control Systems) and EEC 510 (Linear Systems), or permission of instructor

 

Catalog:       

Prerequisite: EEC 510. Artificial intelligence techinques applied to control system design. Topics include fuzzy sets, artificial neural networks, methods for designing fuzzy-logic controllers and neural network controllers; application of computer-aided design techniques for designing fuzzy-logic and neural-network controllers.

 

Textbook:

 J-S. R. Jang, C-T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing, Prentice Hall, 1997, http://mirlab.org/jang/book/

                       

References:

R. A. Aliev and R. R. Aliev, Soft Computing & Its Applications, World Scientific Publishing Company, 2001

 

Clive L. Dym and Raymond E. Levitt, Knowledge-Based Systems in Engineering, McGraw-Hill, 1991

 

Adrian A. Hopgood, Knowledge-Based Systems for Engineers and Scientists, CRC Press, 1993

 

Stamatios V. Kartalopoulos, Understanding Neural Networks and Fuzzy Logic: Basic Concepts and Applications, Wiley-IEEE Press, 1995

 

Vojislav Kecman, Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models, The MIT Press, 2001

 

Amit Konar, Computational Intelligence: Principles, Techniques and Applications, Springer, 2005

 

T. Nanayakkara, F. Sahin, and M. Jamshidi, Intelligent Control Systems with an Introduction to Systems of Systems, CRC Press, 2008

 

Sankar K. Pal and Sushmita Mitra, Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing, John Wiley & Sons, 1999

 

Antonio Ruano, Intelligent Control Systems Using Computational Intelligence Techniques, Institution of Engineering and Technology, 2005

 

Y. Sin and C. Xu, Intelligent Systems: Modeling, Optimization, and Control, CRC Press, 2008

 

Lefteri H. Tsoukalas and Robert E. Uhrig, Fuzzy and Neural Approaches in Engineering, Wiley-Interscience, 1997

 

Objectives:   Students completing this course will obtain a basic understanding of fuzzy logic systems and artificial neural networks, and will know how these techniques are applied to engineering problems, including control systems. Students will understand the advantages and disadvantages of these methods relative to other control methods. Students will be aware of current research trends and issues. Students will be able to design control systems using fuzzy logic and artificial neural networks.

 

Grading

Masters

Doctoral

Homework

25%

20%

Midterm

25%

20%

Term Project

25%

20%

Final Exam

25%

20%

Technical Paper

--

20%

 

Homework: Homework assignments will be posted at http://academic.csuohio.edu/simond/courses/eec645/homework.html. It each studentís responsibility to keep track of the homework assignments and due dates.

 

Doctoral Students: Doctoral students are required to write a technical paper appropriate for journal submission.

 

Paper Submission: Students should submit their term project and technical paper at www.turnitin.com. This web site will help us make sure that the assignments do not contain any plagiarism. The class id is 3421538 and the password is neurofuzzy.

 

Schedule:

Chapter 1: Introduction

Chapter1.docx

Chapter 2: Fuzzy Sets

ch02.ppt

Chapter 3: Fuzzy Rules and Fuzzy Reasoning

ch03.ppt

Chapter 4: Fuzzy Inference Systems

ch04.ppt

Fuzzy Control

FuzzyControl.ppt

CruiseControl.zip

Chapter 6: Derivative-Based Optimization

ch06.ppt

Derivative-Based Fuzzy System Optimization

DerivFuzzyOpt.ppt

Chapter 7: Derivative-Free Optimization

GA.ppt

BBO.ppt

DerivFree.zip

FuzzyBBO.ppt

Chapter 8: Adaptive Networks

Chapter 9: Supervised Learning Neural Nets

NeuralNets.ppt

Neural.zip

Chapter 17: Neuro-Fuzzy Control I
Chapter 18: Neuro-Fuzzy Control II

NeuralControl.ppt

Neural Networks: Additional Topics

NeuralNets2.ppt

NeuralNets3.ppt

NeuroFuzzy.zip

Kohonen.m

LVQ1.m

LVQ2.m

LVQ3.m

NeuralNets4.ppt

 

 


Professor Simonís Home Page

Department of Electrical and Computer Engineering

Cleveland State University


Last Revised: November 18, 2010