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Multi-parameter sensitivity analysis and application research in the robust optimization design for complex nonlinear system

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Abstract

The current research of complex nonlinear system robust optimization mainly focuses on the features of design parameters, such as probability density functions, boundary conditions, etc. After parameters study, high-dimensional curve or robust control design is used to find an accurate robust solution. However, there may exist complex interaction between parameters and practical engineering system. With the increase of the number of parameters, it is getting hard to determine high-dimensional curves and robust control methods, thus it’s difficult to get the robust design solutions. In this paper, a method of global sensitivity analysis based on divided variables in groups is proposed. By making relevant variables in one group and keeping each other independent among sets of variables, global sensitivity analysis is conducted in grouped variables and the importance of parameters is evaluated by calculating the contribution value of each parameter to the total variance of system response. By ranking the importance of input parameters, relatively important parameters are chosen to conduct robust design analysis of the system. By applying this method to the robust optimization design of a real complex nonlinear system-a vehicle occupant restraint system with multi-parameter, good solution is gained and the response variance of the objective function is reduced to 0.01, which indicates that the robustness of the occupant restraint system is improved in a great degree and the method is effective and valuable for the robust design of complex nonlinear system. This research proposes a new method which can be used to obtain solutions for complex nonlinear system robust design.

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Authors and Affiliations

  1. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, 410082, China

    Tao Ma, Weigang Zhang, Yang Zhang & Ting Tang

Authors
  1. Tao Ma
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  2. Weigang Zhang
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  3. Yang Zhang
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  4. Ting Tang
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Corresponding author

Correspondence to Tao Ma.

Additional information

Supported by National Natural Science Foundation of China (Grant No. 51275164)

MA Tao, born in 1989, is a master student at State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, China. His research interests include parameter match design and robust optimization of occupant restraint system.

ZHANG Weigang, born in 1966, is currently a professor at Hunan University, China. He received his PhD degree from Hunan University, China, in 2002. His research interests include theory and methods of vehicle crash.

ZHANG Yang, born in 1987, is a master student at State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, China. Her research interests include parameter analysis and optimization of occupant restraint system.

TANG Ting, born in 1988, is a master student at State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, China. Her research interests include analysis and optimization of occupant restraint system.

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Ma, T., Zhang, W., Zhang, Y. et al. Multi-parameter sensitivity analysis and application research in the robust optimization design for complex nonlinear system. Chin. J. Mech. Eng. 28, 55–62 (2015). https://doi.org/10.3901/CJME.2014.1107.164

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  • DOI: https://doi.org/10.3901/CJME.2014.1107.164

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