NDLI: Neural networks and fuzzy logic in electrical engineering

Content Provider	IEEE Xplore Digital Library
Author	Jurado, F. Ogayar, B. Castro, M. Carpio, J.
Copyright Year	2001
Abstract	Control system packages have become essential ingredients of both undergraduate and graduate courses in the control area. This work describes our experience with the use of MATLAB/sup TM/ with its fuzzy logic and neural networks toolboxes in electrical engineering control courses. While some of the methods in the area of intelligent systems and control have significant benefits to offer, engineers are often reluctant to utilize new intelligent control techniques for several reasons. Two fuzzy logic controllers for a gas turbine have been developed using speed and mechanical power deviations. A neural network has been designed to tune the gains of the fuzzy logic controllers based on the operating conditions of the electric power plant. Student feedback indicates that theoretical developments in lectures on control systems were only appreciated after the laboratory exercises.
Sponsorship	Gen. Electr. Company
Starting Page	975
Ending Page	980
File Size	500140
Page Count	6
File Format	PDF
ISBN	0780367154
ISSN	08407789
DOI	10.1109/CCECE.2001.933575
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-05-13
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Fuzzy logic Electrical engineering Control systems Intelligent control Packaging MATLAB Intelligent systems Power engineering and energy Turbines
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Hardware and Architecture

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Intelligent control based maximum power extraction strategy for wind energy conversion systems

A hybrid intelligent system architecture for utility demand forecasting

Experimental study of SPSA approach to intelligent control systems

Experience with neural networks and fuzzy logic in an electrical engineering control course

Expert system, fuzzy logic, and neural network applications in power electronics and motion control

A Generic Architecture for Intelligent System Hardware

The development of a fuzzy neural system for load forecasting

A fuzzy logic framework for control of switched capacitors in distribution systems

Fuzzy logic controlled multilayer neural networks: theory and case studies

Neural networks and fuzzy logic in electrical engineering

Similar Documents

Intelligent control based maximum power extraction strategy for wind energy conversion systems

A hybrid intelligent system architecture for utility demand forecasting

Experimental study of SPSA approach to intelligent control systems

Experience with neural networks and fuzzy logic in an electrical engineering control course

Expert system, fuzzy logic, and neural network applications in power electronics and motion control

A Generic Architecture for Intelligent System Hardware

The development of a fuzzy neural system for load forecasting

A fuzzy logic framework for control of switched capacitors in distribution systems

Fuzzy logic controlled multilayer neural networks: theory and case studies

Neural networks and fuzzy logic in electrical engineering