基于关键变量分离的输入非线性受控自回归系统最小二乘参数估计
Least Squares Parameter Estimation for Input Nonlinear Controlled Autoregressive Systems Based on the Key Variable Separation
-
摘要: 针对输入非线性系统存在两个未知参数集乘积项，导致模型参数不可辨识的情况，采用规范化系统参数方法来分离关键变量，提出了最小二乘迭代参数估计算法，来辨识输入非线性受控自回归系统的参数．仿真结果验证了其有效性．Abstract: There exists the product of two unknown parameter sets in input nonlinear systems. Thus, the model parameters are unidentifiable. By normalizing the system parameters and using key variable separation, a least squares-based iterative algorithm is proposed to identify input nonlinear controlled autoregressive systems. The proposed algorithm is verified by simulation examples.
下载:
