System-level synthesis of MEMS via genetic programming and bond graphs

  • Authors:

  • Zhun Fan;Kisung Seo;Jianjun Hu;Ronald C. Rosenberg;Erik D. Goodman

  • Affiliations:

  • Genetic Algorithms Research and Applications Group, Michigan State University, East Lansing, MI;Genetic Algorithms Research and Applications Group, Michigan State University, East Lansing, MI;Genetic Algorithms Research and Applications Group, Michigan State University, East Lansing, MI;Department of Mechanical Engineering, Michigan State University, East Lansing, MI;Genetic Algorithms Research and Applications Group, Michigan State University, East Lansing, MI

  • Venue:
  • GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
  • Year:
  • 2003

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Abstract

Initial results have been achieved for automatic synthesis of MEMS system-level lumped parameter models using genetic programming and bond graphs. This paper first discusses the necessity of narrowing the problem of MEMS synthesis into a certain specific application domain, e.g., RF MEM devices. Then the paper briefly introduces the flow of a structured MEMS design process and points out that system-level lumped-parameter model synthesis is the first step of the MEMS synthesis process. Bond graphs can be used to represent a system-level model of a MEM system. As an example, building blocks of RF MEM devices are selected carefully and their bond graph representations are obtained. After a proper and realizable function set to operate on that category of building blocks is defined, genetic programming can evolve both the topologies and parameters of corresponding RF MEM devices to meet predefined design specifications. Adaptive fitness definition is used to better direct the search process of genetic programming. Experimental results demonstrate the feasibility of the approach as a first step of an automated MEMS synthesis process. Some methods to extend the approach are also discussed.