• CN:11-2187/TH
  • ISSN:0577-6686

›› 1999, Vol. 35 ›› Issue (6): 17-20.

• 论文 • 上一篇    下一篇

基于模糊优化下离散误差非线性参数识别方法研究

吴长智;杨庆佛;熊诗波   

  1. 太原理工大学计算中心机械电子工程研究所
  • 发布日期:1999-11-01

STUDY ON NONLINEAR PARAMETER IDENTIFICATION METHOD OF DISPERSIVE ERROR SIGNAL BASED ON FUZZY OPTIMIZATION

Wu Changzhi;Yang Qingfo;Xiong Shibo   

  1. Taiyuan University of Technolog
  • Published:1999-11-01

摘要: 根据结构系统动态特性分析的模糊性,试验测试数据和离散误差选择的模糊性,提出了一种基于模糊优化下解决离散误差信号非线性参数识别的思想和方法。根据模糊数学权函数理论,建立模糊优化函数,推导出一种适用于动态结构系统响应信号高精度参数识别方法——离散误差信号模糊优化非线性参数识别算法。作为实例,对MG1432B整机的动态特性进行模糊分析,并将其响应信号测试数据进行模糊优化非线性参数识别,从而精确地识别出九阶模态参数,并绘出相应点的幅、相频拟合曲线。验证结果说明,此方法具有较高的识别精度和工程应用价值。

关键词: 非线性, 离散误差, 模糊优化, 信号处理

Abstract: In allusion to the analysis fuzzification in dynamic coupling structure system and the test fuzzification in the selection of response signal and dispersive error, an idea and method of new dynamic optimization design is presented, which is used to identify nonlinear parameter of dispersive error signal based on fuzzy optimization. According to the theory of weight function of fuzzy mathematics, the function of fuzzy optimization is established, and an algorithm of highly accurate nonlinear parameter identification is deduced, which is called fuzzy optimization algorithm of dispersive error signal. As a practical example, the dynamic response signal of MG1432B is analysed fuzzily, the dispersive error signal is identified out, the 9th modal parameters are gotten accurately, and the fitting curves of amplitude-frequency and phase-frequency are drawn. The result shows that the method of fuzzy optimization is of higher identification accuracy and wide applied value.

Key words: Dispersive error, Fuzzy optimization, Nonlinear, Signal processing

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