Robust Mechanism Synthesis with Random and Interval Variables

Abstract

Robust mechanism synthesis minimizes the impact of uncertainties on the mechanism performance. It has traditionally been performed by either a probabilistic approach or a worst case approach. Both approaches treat uncertainty as either random variables or interval variables. In reality, uncertainty can be a mixture of both. In this paper, methods are developed for robustness assessment and robust mechanism synthesis when random and interval variables are involved. Monte Carlo simulation is used to perform robustness assessment under an optimization framework for mechanism synthesis.

Department(s)

Mechanical and Aerospace Engineering

Sponsor(s)

Missouri University of Science and Technology. Intelligent Systems Center
National Natural Science Foundation (China)
National Science Foundation (U.S.)

Keywords and Phrases

Optimization; Robustness; Synthesis

International Standard Serial Number (ISSN)

0094-114X

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2009 Elsevier, All rights reserved.

Publication Date

01 Jul 2009

Link to Full Text

Share

 
COinS