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

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@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.",
• notes = "https://www.nsf.gov/awardsearch/showAward?AWD_ID=0101000",

}

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

Citations