Mechatronic Design Evolution Using Bond Graphs and Hybrid Genetic Algorithm With Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Saeed Behbahani and Clarence W. {de Silva}",
  title =        "Mechatronic Design Evolution Using Bond Graphs and
                 Hybrid Genetic Algorithm With Genetic Programming",
  journal =      "IEEE/ASME Transactions on Mechatronics",
  year =         "2013",
  volume =       "18",
  number =       "1",
  pages =        "190--199",
  month =        feb,
  keywords =     "genetic algorithms, genetic programming, Bond graphs,
                 electrohydraulic systems",
  ISSN =         "1083-4435",
  DOI =          "doi:10.1109/TMECH.2011.2165958",
  size =         "10 pages",
  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
  notes =        "Also known as \cite{6029337}",

Genetic Programming entries for Saeed Behbahani Clarence W de Silva