Simple Neuron-Fuzzy Tool for Small Control Devices

Per Printz Madsen

doi:10.1109/ICIEA.2008.4582496

Simple Neuron-Fuzzy Tool for Small Control Devices

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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Abstract

Små kontrol computere der afvikler forskellige former for Fuzzy kontrollere bliver mere og mere udbredte i mange typer udstyr fra husholdningsmaskiner til stor industrielle systemer. Formålet med denne artikel er, for det først, at beskrive et ''easy to use'' tool til implementering af selvlærende fuzzy systemer og for det andet at give et eksempel på anvendelsen af dette tool. Fuzzy systemet er de så kaldet FuNNy system. FuNNy består af en kompiler der kan oversætte et definitions sprog til et fuzzy system i C, samt et learning library i C. Eksemplet er baseret på et simpelt brusebadseksempel. Dette eksempel viser at FuNNy er nemt at bruge og at FuNNy er i stand til at lære at regulere flowet af det varme og kold vand således at der kompenseres for forstyrrelser med en minimal udløbetemperatur variation til følge.

Originalsprog	Engelsk
Titel	3rd IEEE Conference on Industrial Electronics and Applications, 2008. ICIEA 2008
Antal sider	5
Forlag	IEEE
Publikationsdato	2008
Sider	148-152
ISBN (Trykt)	978-1-4244-1717-9
DOI	https://doi.org/10.1109/ICIEA.2008.4582496
Status	Udgivet - 2008
Begivenhed	The 3rd IEEE Conference on Industrial Electronics and Applications (ICIEA 2008) - , Singapore Varighed: 3 jun. 2008 → 5 jun. 2008

Konference

Konference	The 3rd IEEE Conference on Industrial Electronics and Applications (ICIEA 2008)
Land/Område	Singapore
Periode	03/06/2008 → 05/06/2008

Emneord

Fuzzy Control
Fuzzy Learning

Adgang til dokumentet

10.1109/ICIEA.2008.4582496

FuNNy2Forlagets udgivne version, 211 KB

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Citationsformater

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title = "Simple Neuron-Fuzzy Tool for Small Control Devices",

abstract = "Small control computers, running a kind of Fuzzy controller, are more and more used in many systems from household machines to large industrial systems. The purpose of this paper is firstly to describe a tool that is easy to use for implementing self learning Fuzzy systems, that can be executed in a large group of micro computers and secondly to illustrate the use of the tool by an example. The tool is called FuNNy. FuNNy generates Fuzzy systems and consists of a compiler and a C learning library. The compiler translates a Fuzzy system (written in a dedicated language, called FuNNy language) to C. The C learning library contains the learning algorithm. The generated C code is simple standard C and therefore it can be applied to all computers which can be programmed in C. The learning algorithm is a gradient descend method based on a numerical calculation of the gradient. The input fuzzyfication can be described by four different kinds of membership functions. The output fuzzyfication is based on singletons. The rule base can be written in a natural language. The result of the learning is a new version of the Fuzzy system described in the FuNNy language. A simple shower control example is shown. This example shows that FuNNy is able to control the shower and that the learning is able to optimize the Fuzzy system.",

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N2 - Small control computers, running a kind of Fuzzy controller, are more and more used in many systems from household machines to large industrial systems. The purpose of this paper is firstly to describe a tool that is easy to use for implementing self learning Fuzzy systems, that can be executed in a large group of micro computers and secondly to illustrate the use of the tool by an example. The tool is called FuNNy. FuNNy generates Fuzzy systems and consists of a compiler and a C learning library. The compiler translates a Fuzzy system (written in a dedicated language, called FuNNy language) to C. The C learning library contains the learning algorithm. The generated C code is simple standard C and therefore it can be applied to all computers which can be programmed in C. The learning algorithm is a gradient descend method based on a numerical calculation of the gradient. The input fuzzyfication can be described by four different kinds of membership functions. The output fuzzyfication is based on singletons. The rule base can be written in a natural language. The result of the learning is a new version of the Fuzzy system described in the FuNNy language. A simple shower control example is shown. This example shows that FuNNy is able to control the shower and that the learning is able to optimize the Fuzzy system.

AB - Small control computers, running a kind of Fuzzy controller, are more and more used in many systems from household machines to large industrial systems. The purpose of this paper is firstly to describe a tool that is easy to use for implementing self learning Fuzzy systems, that can be executed in a large group of micro computers and secondly to illustrate the use of the tool by an example. The tool is called FuNNy. FuNNy generates Fuzzy systems and consists of a compiler and a C learning library. The compiler translates a Fuzzy system (written in a dedicated language, called FuNNy language) to C. The C learning library contains the learning algorithm. The generated C code is simple standard C and therefore it can be applied to all computers which can be programmed in C. The learning algorithm is a gradient descend method based on a numerical calculation of the gradient. The input fuzzyfication can be described by four different kinds of membership functions. The output fuzzyfication is based on singletons. The rule base can be written in a natural language. The result of the learning is a new version of the Fuzzy system described in the FuNNy language. A simple shower control example is shown. This example shows that FuNNy is able to control the shower and that the learning is able to optimize the Fuzzy system.

KW - Fuzzy Control

KW - Fuzzy Learning

KW - Fuzzy Control

KW - Fuzzy Learning

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DO - 10.1109/ICIEA.2008.4582496

M3 - Article in proceeding

SN - 978-1-4244-1717-9

SP - 148

EP - 152

BT - 3rd IEEE Conference on Industrial Electronics and Applications, 2008. ICIEA 2008

PB - IEEE

T2 - The 3rd IEEE Conference on Industrial Electronics and Applications (ICIEA 2008)

Y2 - 3 June 2008 through 5 June 2008

ER -

Simple Neuron-Fuzzy Tool for Small Control Devices

Abstract

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