Non-linear model reduction by genetic algorithms with using a system structure related fitness function

Maik Buttelmann; Boris Lohmann

doi:10.23919/ecc.2001.7076194

Non-linear model reduction by genetic algorithms with using a system structure related fitness function

Maik Buttelmann, Boris Lohmann

University of Bremen

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

5 Scopus citations

Abstract

Based on a known order reduction method for non-linear systems a solution is proposed to reduce the high system complexity of the order-reduced system, too. For this, suitable secondary conditions for the order reduction method are defined with the help of a genetic algorithm (GA). For the use of GA it is essential that the fitness function fulfils some 'smoothness' or 'small causes, small effects' properties. This is investigated for a system structure related fitness function and an example with technical background is given.

Original language	English
Title of host publication	2001 European Control Conference, ECC 2001
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1870-1875
Number of pages	6
ISBN (Electronic)	9783952417362
DOIs	https://doi.org/10.23919/ecc.2001.7076194
State	Published - 2001
Externally published	Yes
Event	6th European Control Conference, ECC 2001 - Porto, Portugal Duration: 4 Sep 2001 → 7 Sep 2001

Publication series

Name	2001 European Control Conference, ECC 2001

Conference

Conference	6th European Control Conference, ECC 2001
Country/Territory	Portugal
City	Porto
Period	4/09/01 → 7/09/01

Keywords

Fitness Landscape
Genetic Algorithm
Model Simplification
Order Reduction
Structure of Non-linear Systems

Access to Document

10.23919/ecc.2001.7076194

Cite this

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title = "Non-linear model reduction by genetic algorithms with using a system structure related fitness function",

abstract = "Based on a known order reduction method for non-linear systems a solution is proposed to reduce the high system complexity of the order-reduced system, too. For this, suitable secondary conditions for the order reduction method are defined with the help of a genetic algorithm (GA). For the use of GA it is essential that the fitness function fulfils some 'smoothness' or 'small causes, small effects' properties. This is investigated for a system structure related fitness function and an example with technical background is given.",

keywords = "Fitness Landscape, Genetic Algorithm, Model Simplification, Order Reduction, Structure of Non-linear Systems",

author = "Maik Buttelmann and Boris Lohmann",

note = "Publisher Copyright: {\textcopyright} 2001 EUCA.; 6th European Control Conference, ECC 2001 ; Conference date: 04-09-2001 Through 07-09-2001",

year = "2001",

doi = "10.23919/ecc.2001.7076194",

language = "English",

series = "2001 European Control Conference, ECC 2001",

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}

Buttelmann, M & Lohmann, B 2001, Non-linear model reduction by genetic algorithms with using a system structure related fitness function. in 2001 European Control Conference, ECC 2001., 7076194, 2001 European Control Conference, ECC 2001, Institute of Electrical and Electronics Engineers Inc., pp. 1870-1875, 6th European Control Conference, ECC 2001, Porto, Portugal, 4/09/01. https://doi.org/10.23919/ecc.2001.7076194

Non-linear model reduction by genetic algorithms with using a system structure related fitness function. / Buttelmann, Maik; Lohmann, Boris.
2001 European Control Conference, ECC 2001. Institute of Electrical and Electronics Engineers Inc., 2001. p. 1870-1875 7076194 (2001 European Control Conference, ECC 2001).

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

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AU - Lohmann, Boris

PY - 2001

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N2 - Based on a known order reduction method for non-linear systems a solution is proposed to reduce the high system complexity of the order-reduced system, too. For this, suitable secondary conditions for the order reduction method are defined with the help of a genetic algorithm (GA). For the use of GA it is essential that the fitness function fulfils some 'smoothness' or 'small causes, small effects' properties. This is investigated for a system structure related fitness function and an example with technical background is given.

AB - Based on a known order reduction method for non-linear systems a solution is proposed to reduce the high system complexity of the order-reduced system, too. For this, suitable secondary conditions for the order reduction method are defined with the help of a genetic algorithm (GA). For the use of GA it is essential that the fitness function fulfils some 'smoothness' or 'small causes, small effects' properties. This is investigated for a system structure related fitness function and an example with technical background is given.

KW - Fitness Landscape

KW - Genetic Algorithm

KW - Model Simplification

KW - Order Reduction

KW - Structure of Non-linear Systems

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BT - 2001 European Control Conference, ECC 2001

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T2 - 6th European Control Conference, ECC 2001

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ER -

Non-linear model reduction by genetic algorithms with using a system structure related fitness function

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Keywords

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