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Technical Briefs

Variable Sensitivity-Based Deterministic Robust Design for Nonlinear System

[+] Author and Article Information
XinJiang Lu

School of Mechanical and Electrical Engineering, Central South University, Hunan 410083, China; Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kong50008245@student.cityu.edu.hk

Han-Xiong Li

Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, Hong Kongmehxli@cityu.edu.hk

C. L. Philip Chen

Faculty of Science and Technology, University of Macau, Avenue Padre Tomás Pereira, Taipa, Macau, Chinaphilip.chen@ieee.org

J. Mech. Des 132(6), 064502 (May 28, 2010) (7 pages) doi:10.1115/1.4001669 History: Received December 12, 2009; Revised April 27, 2010; Published May 28, 2010; Online May 28, 2010

In this paper, a novel robust design approach is proposed to design the robustness of the nonlinear system under large uncontrollable variation. First, a variable sensitivity approach is proposed to formulate the nonlinear effect into the variable sensitivity matrix. Then, a variable sensitivity-based robust design is developed to minimize the variable sensitivity matrix so that the influence of the uncontrollable variation to the performance will be minimized. Since the proposed robust design considers the influence of the nonlinear term in a large design region, it can effectively improve the robustness of the nonlinear system despite large uncontrollable variation. Simulation examples have demonstrated the effectiveness of the proposed design method.

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Copyright © 2010 by American Society of Mechanical Engineers
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Figures

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Figure 1

(a) Robust design for a weakly nonlinear system; (b) robust design for a strongly nonlinear system

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Figure 2

Variable sensitivity-based robust design methodology

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Figure 3

Variable sensitivity approach

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Figure 4

Robust design for the same sign of Jmax and Jmin

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Figure 5

Robust design for the different signs of Jmax and Jmin

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Figure 6

A set of sensitivity ellipsoids

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Figure 7

Flowchart of the proposed robust design

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Figure 8

Comparison under different variation bounds

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Figure 11

Comparison under different variation bounds

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