Fuzzy control of uncertain nonlinear systems with numerical techniques: a survey

Raheleh Jafari, Sina Razvarz, Alexander Gegov, Wen Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

This paper provides an overview of numerical methods in order to solve fuzzy equations (FEs). It focuses on different numerical methodologies to solve FEs, dual fuzzy equations (DFEs), fuzzy differential equations (FDEs) and partial fuzzy differential equations (PFDEs). The solutions which are produced by these equations are taken to be the controllers. This paper also analyzes the existence of the roots of FEs and some important implementation problems. Finally, several examples are reviewed with different methods.
Original languageEnglish
Title of host publicationAdvances in Computational Intelligence Systems
Subtitle of host publicationContributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK
EditorsZhaojie Ju, Longzhi Yang, Chenguang Yang, Alexander Gegov, Dalin Zhou
PublisherSpringer
Pages3-14
ISBN (Electronic)978-3-030-29933-0
ISBN (Print)978-3-030-29932-3
DOIs
Publication statusPublished - Sep 2019
Event19th UK Workshop on Computational Intelligence - Portsmouth, United Kingdom
Duration: 4 Sep 20195 Sep 2019
Conference number: 19
https://www.ukci2019.port.ac.uk/

Publication series

NameAdvances in Computational Intelligence Systems
PublisherSpringer
Volume1043
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Workshop

Workshop19th UK Workshop on Computational Intelligence
Abbreviated titleUKCI 2019
Country/TerritoryUnited Kingdom
CityPortsmouth
Period4/09/195/09/19
OtherThe UKCI 2019 covers both theory and applications in computational intelligence. The topics of interest include
Fuzzy Systems
Neural Networks
Evolutionary Computation
Evolving Systems
Machine Learning
Data Mining
Cognitive Computing
Intelligent Robotics
Hybrid Methods
Deep Learning
Applications of Computational Intelligence
Internet address

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