Mechatronic Design Evolution Using Bond Graphs and Hybrid Genetic Algorithm With Genetic Programming
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gp-bibliography.bib Revision:1.8098
- @Article{Behbahani:2012:transMechtron,
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author = "Saeed Behbahani and Clarence W. {de Silva}",
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title = "Mechatronic Design Evolution Using Bond Graphs and
Hybrid Genetic Algorithm With Genetic Programming",
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journal = "IEEE/ASME Transactions on Mechatronics",
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year = "2013",
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volume = "18",
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number = "1",
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pages = "190--199",
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month = feb,
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keywords = "genetic algorithms, genetic programming, Bond graphs,
electrohydraulic systems",
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ISSN = "1083-4435",
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DOI = "doi:10.1109/TMECH.2011.2165958",
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size = "10 pages",
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abstract = "A typical mechatronic problem (modelling,
identification, and design) entails finding the best
system topology as well as the associated parameter
values. The solution requires concurrent and integrated
methodologies and tools based on the latest theories.
The experience on natural evolution of an engineering
system indicates that the system topology evolves at a
much slower rate than the parametric values. This paper
proposes a two-loop evolutionary tool, using a hybrid
of genetic algorithm (GA) and genetic programming (GP)
for design optimisation of a mechatronic system.
Specifically, GP is used for topology optimization,
while GA is responsible for finding the elite solution
within each topology proposed by GP. A memory feature
is incorporated with the GP process to avoid the
generation of repeated topologies, a common drawback of
GP topology exploration. The synergic integration of GA
with GP, along with the memory feature, provides a
powerful search ability, which has been integrated with
bond graphs (BG) for mechatronic model exploration. The
software developed using this approach provides a
unified tool for concurrent, integrated, and autonomous
topological realisation of a mechatronic problem. It
finds the best solution (topology and parameters)
starting from an abstract statement of the problem. It
is able to carry out the process of system
configuration realization, which is normally performed
by human experts. The performance of the software tool
is validated by applying it to mechatronic design
problems.",
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notes = "Also known as \cite{6029337}",
- }
Genetic Programming entries for
Saeed Behbahani
Clarence W de Silva
Citations