Neuro-Fuzzy Control Systems

Mechanical Engineering |

Description

Introduction and different architectures of neural networks and N.N. Control. Introduction to fuzzy logic and fuzzy logic controls.

Program

Master of Engineering (MEng) Program

Objectives

Students completing this course will obtain a basic understanding of fuzzy logic systems and artificial neural networks and will know these techniques are applied to control systems.

Textbook

Data will be available soon!

Course Content

content serial

Description

1	Artificial neuron.
2	Back propagation.
3	Hope field networks.
4	Kohonen self-organizing maps.
5	Schemes of neuro control.
6	Identification and control of dynamical systems.
7	Fuzzy stes and fuzzy relations.
8	Fuzzy rules and fuzzy algorithm.
9	Fuzzy logic controller.
10	Fuzzification and defuzzification interfaces.
11	Decision making logic.
12	Design of fuzzy logic controller.
13	Optimization of membership and rule base of fuzzy logic controller using neural networks.
14	Optimization of membership and rule base of fuzzy logic controller using neural networks.
15	Fuzzy neuron.
16	Final Exam.

Markets and Career

Generation, transmission, distribution and utilization of electrical power for public and private sectors to secure both continuous and emergency demands.
Electrical power feeding for civil and military marine and aviation utilities.
Electrical works in construction engineering.

Degree Master
Code: EE713
Credit hrs: 3
Prequisites:

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