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

Raheleh  Jafari; Sina  Razvarz; Alexander Gegov; Wen Yu

doi:10.1007/978-3-030-29933-0_1

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 proceeding › Conference contribution

296 Downloads (Pure)

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 language	English
Title of host publication	Advances in Computational Intelligence Systems
Subtitle of host publication	Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK
Editors	Zhaojie Ju, Longzhi Yang, Chenguang Yang, Alexander Gegov, Dalin Zhou
Publisher	Springer
Pages	3-14
ISBN (Electronic)	978-3-030-29933-0
ISBN (Print)	978-3-030-29932-3
DOIs	https://doi.org/10.1007/978-3-030-29933-0_1
Publication status	Published - Sept 2019
Event	19th UK Workshop on Computational Intelligence - Portsmouth, United Kingdom Duration: 4 Sept 2019 → 5 Sept 2019 Conference number: 19 https://www.ukci2019.port.ac.uk/

Publication series

Name	Advances in Computational Intelligence Systems
Publisher	Springer
Volume	1043
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Workshop

Workshop	19th UK Workshop on Computational Intelligence
Abbreviated title	UKCI 2019
Country/Territory	United Kingdom
City	Portsmouth
Period	4/09/19 → 5/09/19
Other	The 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	https://www.ukci2019.port.ac.uk/

Access to Document

10.1007/978-3-030-29933-0_1

Fuzzy Control of Uncertain Nonlinear Systems
The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-29933-0_1.
Accepted author manuscript (Post-print), 173 KB

Cite this

Jafari, R., Razvarz, S., Gegov, A., & Yu, W. (2019). Fuzzy control of uncertain nonlinear systems with numerical techniques: a survey. In Z. Ju, L. Yang, C. Yang, A. Gegov, & D. Zhou (Eds.), Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK (pp. 3-14). (Advances in Computational Intelligence Systems; Vol. 1043). Springer. https://doi.org/10.1007/978-3-030-29933-0_1

Jafari, Raheleh ; Razvarz, Sina ; Gegov, Alexander et al. / Fuzzy control of uncertain nonlinear systems with numerical techniques: a survey. Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK. editor / Zhaojie Ju ; Longzhi Yang ; Chenguang Yang ; Alexander Gegov ; Dalin Zhou. Springer, 2019. pp. 3-14 (Advances in Computational Intelligence Systems).

@inproceedings{c09396dc77e149e8b5fb100624e65615,

title = "Fuzzy control of uncertain nonlinear systems with numerical techniques: a survey",

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.",

author = "Raheleh Jafari and Sina Razvarz and Alexander Gegov and Wen Yu",

year = "2019",

month = sep,

doi = "10.1007/978-3-030-29933-0\_1",

language = "English",

isbn = "978-3-030-29932-3",

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pages = "3--14",

editor = "Ju, \{Zhaojie \} and Yang, \{Longzhi \} and Chenguang Yang and Gegov, \{Alexander \} and Dalin Zhou",

booktitle = "Advances in Computational Intelligence Systems",

address = "Netherlands",

note = "19th UK Workshop on Computational Intelligence, UKCI 2019 ; Conference date: 04-09-2019 Through 05-09-2019",

url = "https://www.ukci2019.port.ac.uk/",

}

Jafari, R, Razvarz, S, Gegov, A & Yu, W 2019, Fuzzy control of uncertain nonlinear systems with numerical techniques: a survey. in Z Ju, L Yang, C Yang, A Gegov & D Zhou (eds), Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK. Advances in Computational Intelligence Systems, vol. 1043, Springer, pp. 3-14, 19th UK Workshop on Computational Intelligence, Portsmouth, United Kingdom, 4/09/19. https://doi.org/10.1007/978-3-030-29933-0_1

Fuzzy control of uncertain nonlinear systems with numerical techniques: a survey. / Jafari, Raheleh ; Razvarz, Sina ; Gegov, Alexander et al.
Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK. ed. / Zhaojie Ju; Longzhi Yang; Chenguang Yang; Alexander Gegov; Dalin Zhou. Springer, 2019. p. 3-14 (Advances in Computational Intelligence Systems; Vol. 1043).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Fuzzy control of uncertain nonlinear systems with numerical techniques: a survey

AU - Jafari, Raheleh

AU - Razvarz, Sina

AU - Gegov, Alexander

AU - Yu, Wen

N1 - Conference code: 19

PY - 2019/9

Y1 - 2019/9

N2 - 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.

AB - 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.

U2 - 10.1007/978-3-030-29933-0_1

DO - 10.1007/978-3-030-29933-0_1

M3 - Conference contribution

SN - 978-3-030-29932-3

T3 - Advances in Computational Intelligence Systems

SP - 3

EP - 14

BT - Advances in Computational Intelligence Systems

A2 - Ju, Zhaojie

A2 - Yang, Longzhi

A2 - Yang, Chenguang

A2 - Gegov, Alexander

A2 - Zhou, Dalin

PB - Springer

T2 - 19th UK Workshop on Computational Intelligence

Y2 - 4 September 2019 through 5 September 2019

ER -

Jafari R, Razvarz S, Gegov A, Yu W. Fuzzy control of uncertain nonlinear systems with numerical techniques: a survey. In Ju Z, Yang L, Yang C, Gegov A, Zhou D, editors, Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, September 4-6, 2019, Portsmouth, UK. Springer. 2019. p. 3-14. (Advances in Computational Intelligence Systems). Epub 2019 Aug 30. doi: 10.1007/978-3-030-29933-0_1

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

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