辅助模型辨识方法(2):输入非线性输出误差系统

Auxiliary model identification methods. Part B:Input nonlinear output-error systems

针对具有已知基的输入非线性输出误差系统,提出了基于过参数化模型的辅助模型递推辨识方法和辅助模型递阶辨识方法,提出了基于关键项分离的辅助模型递推辨识方法、基于关键项分离的辅助模型两阶段辨识方法和辅助模型三阶段辨识方法,提出了基于双线性参数模型分解的辅助模型随机梯度算法和基于双线性参数模型分解的辅助模型递推最小二乘算法,并给出了几个典型辨识算法的计算量、计算步骤.这些算法的收敛性分析都是需要研究的辨识课题.

For input nonlinear output？error systems with known bases,this paper presents the over？parameterization model based auxiliary model （ AM） recursive identification methods,the over？parameterization model based AM hi？erarchical identification methods,the key term separation based AM recursive identification methods,the key term separation based AM two？stage recursive identification methods,the key term separation based AM three？stage re？cursive identification methods,the bilinear？in？parameter model decomposition based AM stochastic gradient identifi？cation methods and the bilinear？in？parameter model decomposition based AM recursive least squares identification methods.Finally,the computational efficiency and the computational steps of several typical identification algorithms are discussed.The convergence of the proposed algorithms needs further study.