含有过程噪声的Hammerstein-Wiener模型辨识算法及其收敛性分析

针对含有过程噪声的Hammerstein-Wiener模型,提出一种偏差补偿递推最小二乘辨识方法.通过将偏差补偿引入到递推最小二乘算法中,在线辨识包含原系统参数乘积项的参数向量.并用鞅收敛定理证明偏差补偿递推最小二乘辨识算法的收敛性,分析表明在持续激励的条件下参数估计偏差一致收敛于零.仿真结果表明该方法优于递推最小二乘辨识方法.

Identification Algorithm of Hammerstein-Wiener Model with Process Noise and Its Convergence Analysis

A bias-compensated recursive least squares(BCRLS) algorithm was proposed to identify the Hammerstein-Wiener model with process noise,i.e.,the bias compensation was introduced into the recursive least squares algorithm.The parameter vector containing the product of the original system parameters was thus identified on-line.Then,the convergence of the algorithm was proved by the martingale convergence theorem.It was found that the estimation error of parameter product uniformly converges to zero during persis...