计算机集成制造系统 ›› 2020, Vol. 26 ›› Issue (10): 2723-2734.DOI: 10.13196/j.cims.2020.10.012

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基于改进灰色TOPSIS模型的信号—响应系统稳健参数设计

熊晓琼,李智豪,李昇平+   

  1. 汕头大学工学院
  • 出版日期:2020-10-31 发布日期:2020-10-31
  • 基金资助:
    国家自然科学基金资助项目(61573233,51175315);广东省自然科学基金重点资助项目(2015A030311017)。

Robust parameter design for signal-response systems using improved grey-TOPSIS model

  • Online:2020-10-31 Published:2020-10-31
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.61573233,51175315),and the Natural Science Foundation of Guangdong Province,China(No.2015A030311017).

摘要: 为解决具有多个响应变量的信号—响应系统的稳健参数设计问题,提出一种以田口方法为基础,将灰色关联分析法和逼近理想解排序法相结合的实现方法。运用主成分分析法,采取只消除相关性但不降维的策略来处理响应变量之间的关联冲突问题;用欧氏距离和灰色关联度的加权组合替代欧氏距离,建立改进的灰色逼近理想解排序模型,提出灰色相对贴近度作为稳健性指标,使其能同时反映响应数据序列的位置差异和变化趋势;对灰色相对贴近度进行因子效应分析,从而得到稳健参数设计结果。通过两个算例验证了所提方法的适用性和有效性。

关键词: 信号&mdash, 响应系统, 稳健参数设计, 多响应, 主成分分析, 灰色关联分析, 逼近理想解排序

Abstract: To solve the robust parameter design problem for signal-response systems with multiple responses,a Taguchi-based method combining grey relational analysis and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was proposed.Principal component analysis was used to solve the correlation problem existing among multiple responses by taking the strategy that only eliminates the correlation but not reduce the dimensions.The improved grey-TOPSIS model was established using the weighted combination of Euclidean distance and grey relational degree to replace Euclidean distance,and the grey relative closeness degree was defined as the robustness index,which could reflect the relative position and change trend of the response's data sequences simultaneously.The robust parameter design results could be obtained based on the factor effect analysis of the grey relative closeness degree.The applicability and effectiveness of the proposed method was demonstrated with two engineering examples.The comparison results showed that the proposed method could achieve a better robust solution.

Key words: signal-response systems, robust parameter design, multiple responses, principal component analysis, grey relational analysis, technique for order preference by similarity to an ideal solution

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