Automated Design Methodology for Mechatronic Systems Using Bond Graphs and Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{GARAGe02-01-01,
  author =       "Erik D. Goodman and Kisung Seo and 
                 Ronald C. Rosenberg and Zhun Fan and Jianjun Hu and Baihai Zhang",
  title =        "Automated Design Methodology for Mechatronic Systems
                 Using Bond Graphs and Genetic Programming",
  booktitle =    "Proceedings 2002 NSF Design, Service and Manufacturing
                 Grantees and Research Conference",
  year =         "2002",
  pages =        "206--221",
  address =      "San Juan, Puerto Rico",
  month =        jan,
  organization = "National Science Foundation",
  publisher =    "National Science Foundation",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://garage.cse.msu.edu/papers/GARAGe02-01-01.pdf",
  size =         "16 pages",
  abstract =     "We suggest an automated design methodology for
                 synthesising designs for multi-domain systems, such as
                 mechatronic systems. The domain of mechatronic systems
                 includes mixtures of, for example, electrical,
                 mechanical, hydraulic, pneumatic, and thermal
                 components, making it difficult to design a system to
                 meet specified performance goals with a single design
                 tool. The multi-domain design approach is not only
                 efficient for mixed domain problems, but is also useful
                 for addressing separate single-domain design problems
                 with a single tool. Bond graphs are domain independent,
                 allow free composition, and are efficient for
                 classification and analysis of models, allowing rapid
                 determination of various types of acceptability or
                 feasibility of candidate designs. This can sharply
                 reduce the time needed for analysis of designs that are
                 infeasible or otherwise unattractive. Genetic
                 programming is well recognised as a powerful tool for
                 open-ended search. The combination of these two
                 powerful methods is therefore an appropriate target for
                 a better system for synthesis of complex multi-domain
                 systems. The approach described here will evolve new
                 designs (represented as bond graphs) with
                 ever-improving performance, in an iterative loop of
                 synthesis, analysis, and feedback to the synthesis
                 process. The suggested design methodology has been
                 applied here to two design examples. One is domain
                 independent, an eigenvalues-placement design problem
                 which is tested for some sample target sets of
                 eigenvalues. The other is in the electrical domain --
                 namely, design of analog filters to achieve specified
                 performance over a given frequency range.",
}

Genetic Programming entries for Erik Goodman Kisung Seo Ronald C Rosenberg Zhun Fan Jianjun Hu Baihai Zhang

Citations