基于Adaline的双线性Hammerstein模型在线参数辨识

针对双线性Hammerstein模型，提出一种新的模型参数在线辨识方法。此辨识方法只需简单地改变模型输入，即可在线获得此类非线性模型的一致估计。首先利用伪随机二进制序列输入一致估计出模型中的双线性子系统参数，然后再借助于自适应控制中的一些方法，给模型输入连续信号，利用Adaline一致估计出静态非线性增益。此方法结构简单，计算量小，可快速推导出结果。通过理论分析和仿真研究均说明了该方法的有效性和实用性。

On-line parameter identification of bilinear Hammerstein system using Adaline

A new method of on-line parameter identification of bilinear Hammerstein system is proposed. This method makes consistent estimates of the nonlinear system on-line by changing the input of system simply. Firstly, system is driven by P.R.B.S. to make the consistent estimates of the parameters of bilinear sub-system. Then, system is driven by continuous signal. By means of some idea of adaptive control, Adaline is used to make consistent estimates of the static nonlinear gain of system. With simple computational effort,this method of identification can deduce result fast. The efficiency and applicability of this method is demonstrated by simulation.