Real-Life Applications of Fuzzy Logic

Harpreet Singh,Ashu M. G. Solo,Thomas Meitzler,Kum Kum Garg,Zeng-Guang Hou,Lotfi A. Zadeh,Madan M. Gupta

doi:10.1155/2013/581879

Abstract

1 Department of Electrical and Computer Engineering, Wayne State University, Detroit, MI 48202, USA 2 Intelligent Systems Research Laboratory, College of Engineering, University of Saskatchewan, Saskatoon, SK, Canada S7N 5A9 3 Electrified Armor Lab, RDECOM TARDEC, 6501 E. 11 Mile Road, RDTA-RS, MS 263, Warren, MI 48397-5000, USA 4Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, P.O. Box 2728, Beijing 100190, China 5Manipal University Jaipur, Jaipur 303007, India 6Maverick Technologies America Inc., Suite 808, 1220 North Market Street, Wilmington, DE 19801, USA 7Department of Electrical Engineering and Computer Sciences, University of California Berkeley, CA 94720-1776, USA

Highlights

The theory of fuzzy logic is based on the notion of relative graded membership, as inspired by the processes of human perception and cognition
New computing methods based on fuzzy logic can be used in the development of intelligent systems for decision making, identification, pattern recognition, optimization, and control
Fuzzy logic has been used in numerous applications such as facial pattern recognition, air conditioners, washing machines, vacuum cleaners, antiskid braking systems, transmission systems, control of subway systems and unmanned helicopters, knowledge-based systems for multiobjective optimization of power systems, weather forecasting systems, models for new product pricing or project risk assessment, medical diagnosis and treatment plans, and stock trading

Summary

Introduction

The theory of fuzzy logic is based on the notion of relative graded membership, as inspired by the processes of human perception and cognition. Zadeh published his first famous research paper on fuzzy sets in 1965. New computing methods based on fuzzy logic can be used in the development of intelligent systems for decision making, identification, pattern recognition, optimization, and control. The applications of fuzzy logic, once thought to be an obscure mathematical curiosity, can be found in many engineering and scientific works.

Results

Conclusion