• Corpus ID: 112314974

Neuro-Fuzzy Software for Intelligent Control and Education

  title={Neuro-Fuzzy Software for Intelligent Control and Education},
  author={Erik Joaqu{\'i}n and M. Pegoraro},
The theory of fuzzy sets traces its origins back to 1965 after its introduction by Lotfi A. Zadeh. Twenty years later suffers its greatest breakthrough in the control community and after the years its application has been continuously increasing in many other areas. However, there is still some part of the community that remains doubtful about fuzzy logic potential. Some author point out that this is due the lack of availability of free tool. The present work intends to counteract this trend… 

FEUP fuzzy tool II: Improved tool for education and embedded control

This document briefly describes and validates through some example applications the current release of the toolbox which makes FEUP Fuzzy Tool one of the most complete and advanced fuzzy logic software available.



Twenty years of fuzzy control: experiences gained and lessons learnt

  • E. Mamdani
  • Computer Science
    [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems
  • 1993
It is argued that fuzzy control and allied other techniques such as self-organizing fuzzy control, neural networks, genetic algorithms, and so on, provide an alternate paradigm to the analytic control theory and is based on decision-making approaches from artificial intelligence.

Fuzzy logic in Northern Europe: industrial applications and software developments

  • P. Eklund
  • Computer Science
    Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference
  • 1994
A usage scenario for industrial applications, and software toolkits as developed for and on the basis of the respective industrial needs are presented.

Applications of fuzzy logic and software development in Switzerland

  • J. Hess
  • Computer Science
    Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference
  • 1994
The jury is still out on what fuzzy logic really is, but Switzerland does have a quiet and persistent way to go about its business, especially since the authors know that their friends from Japan are doing exactly that.

GNU Fuzzy

  • Detlef D. Nauck
  • Computer Science
    2007 IEEE International Fuzzy Systems Conference
  • 2007
This paper looks at some of the key considerations that are important for building a fuzzy tool kit that can support the take-up of fuzzy systems in business applications.

A fuzzy inference engine in nonlinear analog mode and its application to a fuzzy logic control

  • T. Yamakawa
  • Computer Science
    IEEE Trans. Neural Networks
  • 1993
In this tutorial, the utility of a fuzzy system is demonstrated by providing a broad overview, emphasizing analog mode hardware, along with a discussion of the author's original work. First, the

Fuzzy control in Germany: a survey

The fuzzy approach stimulates the solution of complicated control problems with the help of experts, who know the process excellently but do not have deep knowledge in the field of system theory, and produces a precise controller operating on the basis of fuzzy knowledge.

The evolution of neuro-fuzzy systems

  • D. NauckA. Nurnberger
  • Computer Science
    NAFIPS 2005 - 2005 Annual Meeting of the North American Fuzzy Information Processing Society
  • 2005
Recalling some milestones on the evolution of neuro-fuzzy systems is briefly recalled.

Hardware implementation versus software emulation of fuzzy algorithms in real applications

  • B. GiacaloneM. L. Lo PrestiF. Di Marco
  • Computer Science
    1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228)
  • 1998
Fuzzy logic has been widely employed in many application areas for the implementation of fuzzy expert and control systems but today fuzzy logic is mainly used to solve nonlinear control problems or in signal processing.

A new methodology for designing a fuzzy logic controller

Application of FLC with these new methodologies is presented for a thermal process with a varying deadtime to show the robust performance of F LC and the effectiveness of these methodologies.

Xfuzzy: a design environment for fuzzy systems

Xfuzzy is a CAD tool that eases the development of fuzzy systems from their conception to their final implementation and includes several synthesis facilities for implementing the system on either software or hardware.