航空学报 > 2009, Vol. 30 Issue (2): 374-379

电液负载模拟器的神经网络参数辨识

张彪,赵克定,孙丰迎   

  1. 哈尔滨工业大学 机电工程学院
  • 收稿日期:2007-11-16 修回日期:2008-04-10 出版日期:2009-02-15 发布日期:2009-02-15
  • 通讯作者: 张彪

Neural Network Parameter Identification of Electro-hydraulic Load Simulator

Zhang Biao, Zhao Keding, Sun Fengying   

  1. School of Mechatronics Engineering, Harbin Institute of Technology
  • Received:2007-11-16 Revised:2008-04-10 Online:2009-02-15 Published:2009-02-15
  • Contact: Zhang Biao

摘要: 基于神经网络,提出一种根据参数上下界辨识系统参数的新方法。在建立电液负载模拟器模型的基础上,在待辨识参数的上下界内,使用神经网络对动态系统的参数进行辨识,找到一组参数使之满足对实际系统的最佳逼近,使系统在实际输入信号下能更好地复现实际系统的实际输出。并使用另一组实验数据检验辨识结果对实际系统的任意实际输入输出采样数据组的逼近程度。验证结果表明该辨识结果能很精确地逼近实际系统。该方法可用于一般复杂系统的实际参数辨识。

关键词: 电液负载模拟器, 神经网络, 参数辨识, 参数界值, 动态模型辨识

Abstract: A new neural network parameter identification method is proposed by using the upper and lower bounds of the parameters of an electro-hydraulic load simulator. First, a mathematical model of the electro-hydraulic load simulator is built; then searching is performed for the best parameter values between the upper and lower bounds of the parameters using the neural network method. The goal is for the output under the inputs of the system to approximate the output of experiments. Finally, the efficiency of the identification parameters is tested by means of another group of experimental data. The result shows that the identification parameters can approximate the real system well. This identification method can be used in the parameter identification of complex dynamic systems.

Key words: electro-hydraulic load simulator, neural networks, parameter identification, parameter bound value, dynamic model identification

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