含饱和特性的双采样率数据Hammerstein系统辨识

针对含有饱和特性的双采样率数据Hammerstein系统提出了一种新的辨识方法。首先，将含有饱和特性的静态非线性环节和线性动态环节的串联，整理成一个非线性基函数和线性动态环节的串联。在此基础上，利用辅助模型辨识原理解决数据缺失、中间未知变量、被辨识参数之间存在耦合的问题, 通过递推辨识算法利用双率采样数据辨识单率Hammerstein模型中的参数。最后，以一个含饱和特性非线性系统实例的建模来验证提出辨识算法的有效性。

Identification of Dual-Rate Sampled Data Nonlinear Systems with Saturation Characteristic Function

A novel identification method of dual-rate sampled data Hammerstein system with saturation characteristic function is proposed. For such nonlinear systems, the series connection of linear dynamic module and static nonlinear module with saturation characteristic function is arranged into the series connection of linear dynamic module and the corresponding nonlinear basis functions. On this basis, the principle of auxiliary model identification is employed to deal with missing sampling data, unknown intermediate variables, and coupling between identified parameters. The recursive identification algorithm is used to estimate the parameters of single rate Hammerstein model by dual-rate sampled data. Finally, the effectiveness of the proposed identification algorithm is verified by building model of a nonlinear system with saturation characteristics.