Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
500162 | Computer Methods in Applied Mechanics and Engineering | 2006 | 13 Pages |
Abstract
A multi-objective optimization (MOO) based methodology is presented to identify simplified dynamic system simulation models. The proposed methodology is used to develop a three degree-of-freedom model for an automotive crash simulation. To date, such system identification problems have only been approached as single-objective problems. We use various MOO methods to provide new insight into the problem. Furthermore, we use this problem to study the nature of the Pareto optimal hypersurface, normalization of objectives, and specification of preferences. In general, we find that the MOO-based methodology is quite useful for dynamic system identification problems.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
R. Timothy Marler, Chang-Hwan Kim, Jasbir S. Arora,