MISO Hammerstein模型识别的新技术

M. Boutayeb, M. Darouach, H. Rafaralahy, G. Krzakala
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引用次数: 11

摘要

本文提出了一种非线性多输入单输出Hammerstein模型的递归辨识方法,该方法是在基本卡尔曼滤波器的基础上发展起来的,它的优点是可以递归地估计非线性系统各子模型的参数,而不需要进行变换,该方法采用了输入输出差分方程的新公式。需要估计的参数数量最少,从而大大减少了计算量。通过一个算例说明了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new technique for identification of MISO Hammerstein model
A recursive method for identfication of nonlinear multi-input single-output Hammerstein model is presented This is developed along the lines of the basic Kalman filter and has the advantage to esimate recursively parameters of each submodel of the nonlinear system without transformation, which is obtained by the use of a new formulation of the input output difference equation. Parameters number to be estimated is minimal and then computational requirements are considerbly reduced. Efficiency of this algorithm is shown by mean of a numerical example.
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