Genetic Algorithm based Optimization approach for MR Dampers Fuzzy Modeling
| Main Authors: | Behnam Mehrkian, Arash Bahar, Ali Chaibakhsh |
|---|---|
| Format: | Article |
| Bahasa: | eng |
| Terbitan: |
, 2011
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/1076968 |
| ctrlnum |
1076968 |
|---|---|
| fullrecord |
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<dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><creator>Behnam Mehrkian</creator><creator>Arash Bahar</creator><creator>Ali Chaibakhsh</creator><date>2011-11-21</date><description>Magneto-rheological (MR) fluid damper is a semiactive
control device that has recently received more attention by the
vibration control community. But inherent hysteretic and highly
nonlinear dynamics of MR fluid damper is one of the challenging
aspects to employ its unique characteristics. The combination of
artificial neural network (ANN) and fuzzy logic system (FLS) have
been used to imitate more precisely the behavior of this device.
However, the derivative-based nature of adaptive networks causes
some deficiencies. Therefore, in this paper, a novel approach that
employ genetic algorithm, as a free-derivative algorithm, to enhance
the capability of fuzzy systems, is proposed. The proposed method
used to model MR damper. The results will be compared with
adaptive neuro-fuzzy inference system (ANFIS) model, which is one
of the well-known approaches in soft computing framework, and two
best parametric models of MR damper. Data are generated based on
benchmark program by applying a number of famous earthquake
records.</description><identifier>https://zenodo.org/record/1076968</identifier><identifier>10.5281/zenodo.1076968</identifier><identifier>oai:zenodo.org:1076968</identifier><language>eng</language><relation>doi:10.5281/zenodo.1076967</relation><relation>url:https://zenodo.org/communities/waset</relation><rights>info:eu-repo/semantics/openAccess</rights><rights>https://creativecommons.org/licenses/by/4.0/legalcode</rights><subject>Benchmark program</subject><subject>earthquake record filtering</subject><subject>fuzzy logic</subject><subject>genetic algorithm</subject><subject>MR damper.</subject><title>Genetic Algorithm based Optimization approach for MR Dampers Fuzzy Modeling</title><type>Journal:Article</type><type>Journal:Article</type><recordID>1076968</recordID></dc>
|
| language |
eng |
| format |
Journal:Article Journal |
| author |
Behnam Mehrkian Arash Bahar Ali Chaibakhsh |
| title |
Genetic Algorithm based Optimization approach for MR Dampers Fuzzy Modeling |
| publishDate |
2011 |
| topic |
Benchmark program earthquake record filtering fuzzy logic genetic algorithm MR damper |
| url |
https://zenodo.org/record/1076968 |
| contents |
Magneto-rheological (MR) fluid damper is a semiactive
control device that has recently received more attention by the
vibration control community. But inherent hysteretic and highly
nonlinear dynamics of MR fluid damper is one of the challenging
aspects to employ its unique characteristics. The combination of
artificial neural network (ANN) and fuzzy logic system (FLS) have
been used to imitate more precisely the behavior of this device.
However, the derivative-based nature of adaptive networks causes
some deficiencies. Therefore, in this paper, a novel approach that
employ genetic algorithm, as a free-derivative algorithm, to enhance
the capability of fuzzy systems, is proposed. The proposed method
used to model MR damper. The results will be compared with
adaptive neuro-fuzzy inference system (ANFIS) model, which is one
of the well-known approaches in soft computing framework, and two
best parametric models of MR damper. Data are generated based on
benchmark program by applying a number of famous earthquake
records. |
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IOS16997 |
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2022-06-06T04:58:19Z |
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17.538404 |