Design Automation of Mechatronic Systems

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

@PhdThesis{ZhunFan:thesis,
  author =       "Zhun Fan",
  title =        "Design Automation of Mechatronic Systems",
  school =       "Electrical and Computer Engineering, Michigan State
                 University",
  year =         "2004",
  address =      "USA",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://search.proquest.com/docview/305157550",
  URL =          "http://www.worldcat.org/title/design-automation-of-mechatronic-systems-using-evolutionary-computation-and-bond-graph/oclc/060353062",
  broken =       "https://www.msu.edu/~fanzhun/Zhun%27s%20Dissertation%20Research.htm",
  size =         "132 pages",
  abstract =     "Design automation is a difficult task and has been
                 studied for some time by researchers. Most research is
                 quite successful in automating the parameters of a
                 given design topology. However, their limitation is
                 that they only accept fixed design topologies. Others
                 can design in topologically unconstrained space, but
                 are limited or specially tailored to a single physical
                 domain. The motivation of this research is two-fold.
                 First, we want to find a way to generate a population
                 of topologically open-ended design alternatives and
                 provide for the designer, in an automated manner, a
                 variety of satisfactory design candidates to choose
                 among and trade off. Second, we want our method to be
                 applicable not only in one physical domain, but in
                 multiple domains or a mixture of them, as is required
                 for design of mechatronic systems. To meet these ends,
                 the capability of genetic programming to search
                 automatically in an open-ended search space and the
                 strong capability of bond graphs to represent and model
                 mixed-domain systems are studied and ways to blend
                 their merits in one unified approach are investigated.
                 In our research, the BG/GP method, combining bond
                 graphs and genetic programming, has been developed to
                 automate the conceptual design process for general
                 multidisciplinary mechatronic systems.

                 Several design problems, in macro- and micro-domains,
                 and in different physical domains, have been used as
                 design examples to test the feasibility of the BG/GP
                 approach. The analog electronic filter design problem
                 shows the efficiency and effectiveness of the proposed
                 approach. A vibration absorber design for a mechanical
                 printer demonstrates that the approach can also be used
                 for redesign and is very effective in exploring in an
                 open-ended topology space and capable of providing
                 designers with a variety of good design candidates for
                 further analysis and tradeoff. A pneumatic air pump
                 design shows how to bias design preference and implies
                 the possibility and significance of extracting design
                 heuristics in the evolutionary process. Finally, a MEM
                 filter design problem shows that the BG/GP approach can
                 be applied in a very general class of conceptual design
                 problems with severe topology and/or parameter
                 constraints. The results show that the BG/GP method is
                 a powerful synergistic approach for automated,
                 mixed-domain, and topologically open-ended design of
                 mechatronic systems.

                 A structured and hierarchical design methodology for
                 Micro-Electro-Mechanical-Systems (MEMS) is also
                 studied. MEMS are actually micro-mechatronic systems.
                 The research of hierarchical evolutionary synthesis of
                 MEMS in this thesis includes the system-level
                 behavioural synthesis and second-level layout synthesis
                 of MEMS. Preliminary results show that automated
                 synthesis of MEMS is a very promising research area.",
  notes =        "SF Project (DMI0084934) NSF Automated Synthesis of
                 Mechatronic Systems by Bond graph and Genetic
                 Programming
                 http://garage.cse.msu.edu/gpbg/index.htm

                 OCLC Number: 60353062. ProQuest 3146015. UMI Microform
                 3146015",
}

Genetic Programming entries for Zhun Fan

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