辅助模型辨识方法(3):输入非线性输出误差自回归系统

Auxiliary model based identification methods.Part C:Input nonlinear output-error autoregressive systems

输入非线性系统包括输入非线性方程误差类系统和输入非线性输出误差类系统.针对输入非线性输出误差自回归系统,分别基于过参数化模型,基于关键项分离原理,基于数据滤波技术,研究了相应的基于过参数化模型的辅助模型递推辨识方法、基于关键项分离的辅助模型递推辨识方法、基于数据滤波的辅助模型递推辨识方法.这些方法可以推广到其他输入非线性输出误差系统、输出非线性输出误差系统、反馈非线性系统等.并给出了几个典型辨识算法的计算步骤、流程图和计算量.

The input nonlinear systems include the input nonlinear equation-error type systems and the input nonlinear output-error type systems.According to the over-parameterization model,the key term separation and the data filtering, this paper studies and presents the over-parameterization model based auxiliary model recursive identification （AM-RI） methods, the key term separation based AM-RI methods and the data filtering based AM-RI methods for input nonlinear output-error autoregressive systems.These methods can be extended to other input nonlinear output-error systems, output nonlinear output-error type systems and feedback nonlinear systems.Finally, the computational efficiency, the computational steps and the flowcharts of several typical identification algorithms are discussed.