Automated Design Methodology for Mechatronic Systems Using Bond Graphs and Genetic Programming精品.pdfVIP
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Automated Design Methodology for Mechatronic Systems Using Bond Graphs and Genetic Programming精品
Automated Design Methodology for Mechatronic Systems
Using Bond Graphs and Genetic Programming
Goodman, Erik D., Genetic Algorithms Research and Applications Group (GARAGe), Case
Center for Computer-Aided Engineering Manufacturing, Michigan State University,
goodman@
Seo, Kisung, Genetic Algorithms Research and Applications Group (GARAGe), Case Center for
Computer-Aided Engineering Manufacturing, Michigan State University, ksseo@
Rosenberg, Ronald C., Department of Mechanical Engineering, Michigan State University,
rosenber@
Fan, Zhun, Electrical and Computer Engineering, Michigan State University,
fanzhun@
Hu, Jianjun, Computer Science and Engineering, Michigan State University,
hujianju@
Zhang, Baihai, Department of Mechanical Engineering, Michigan State University,
zhangbai@
Abstract
This paper suggests an automated design methodology for synthesizing 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 recognized 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 (re
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