top of page

EENG 486 :  Intelligent Control 

The Course also found, over UoB-Blackborad:    or   visit the above LEARNING link


Office Hours :  Any time, please send an e-mail to :

Office No: 14-146-A

Office Location:  College of Engineering, Building 14.

Office Telephone:  ++ 973 17876286,  or  ++ 973 17876606

This Course Goal:  refer to (EENG 486 ABET) Document:

Course code: EENG 486:  Course title:   Intelligent Control


Course credits: 3

Pre-requisites: EENG 381


Course coordinator:  Prof. E. Mattar,  


Course Textbook:

A: Primary Texts:

[1] Rudolf Kruse et al.,  Computational Intelligence: A Methodological Introduction, 2nd Edition,  Springer, New York, 2016.  ISBN 978-1-4471-7294-9
Bookstore or online, e.g., Springer
[2] David Poole and Alan Mackworth "Artificial Intelligence: Foundations of Computational Agents".

Cambridge University Press, (1st edition: 2010, 2nd edition: 2017). (available online. The section references below are to the 2nd edition.)

B: Other Texts:

[3] Stuart Russell and Peter Norvig Artificial Intelligence: A Modern Approach  Pearson Series in Artificial Intelligence, 2020, Fourth Edition,

[4] C: J-S. R. Jang, C-T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing, Prentice Hall, 1997,

[5] Kevin M. Passino and Stephen Yurkovich, Fuzzy Control, Addison Wesley Longman, Menlo Park, CA, 1998.References:  J-S. R. Jang, C-T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing, Prentice Hall, 1997,Other resources used (e.g. e-Learning, field visits, periodicals, software, etc.).


Other resources used (e.g. e-Learning, field visits, periodicals, software, etc.).

To provide the necessary background in nonlinear system analysis and nonlinear control system design for those strongly interested in control system design.



A standard undergraduate-level background in control system design.  The Course will be fully supported by a large number of laboratory experiments and practical works.  

Hence,  a student will learn the basics of  Matlab and use it as a support for analysis and design of lab oriented experiments. 

Course description (from the UOB Catalog):
This course is an introductory course on intelligent control. The main goal of the course is to learn a variety of fuzzy control methods, and to understand how they use a diversity

of heuristic knowledge to achieve control specifications. Basic components and their roles in general fuzzy systems are explained to understand how fuzzy controllers work. Based on the basic idea of fuzzy control, advanced topics in intelligent control, including fuzzy identification, adaptive/supervisory fuzzy control, neural networks, genetic algorithms, expert systems and fuzzy decision making systems, are also covered. Comparisons between fuzzy and conventional control techniques are done, and advantages and disadvantages of each technique will be clarified. Through various examples, students will learn how to apply intelligent control techniques to real engineering problems with Matlab.



Course QAAC Form (course quality sheet for S1-2023-2024)

Samples of Finals, Mid-Terms, Previous Years 

Course Labs_Manual

Course Lab Sessions - List of Equipment, watch the Control Lab Equipment Here,  the Video (press to watch).

Lectures Notes: Access via UoB Blackboard link;  UoB BB course contents.

Object Oriented Programming using Matlab (OOP):

Object Oriented Programming using Matlab (OOP), uses of classes (class), objects (obj) and data structure (struct) .. if you would like to use this approach in programming for this course, this will be great.  This is optional, but it is always good to learn latest and advanced programming tools. 

Download slides about Matlab from the Advanced MATLAB for Scientific Computing, Stanford University.  OOP-Matlab press to download

prereq.  :   

EENG381,  Control Systems  

Coding prereq. :   

Fuzzy AI Algorithms,  Genetics, Neural Net,  Foraging,  Fuzzy-Neural,  Learning Systems,  Evolution,  Sys_Identication (ANN).

bottom of page