基于随机多正弦激励的Wiener-Hammerstein系统估计器初始化

P. Crama, J. Schoukens
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引用次数: 7

摘要

维纳-哈默斯坦系统由一个线性动态系统和一个静态非线性系统组成,然后是另一个线性动态系统。这些模型很难识别,因为存在两个动态系统,它们对系统行为的贡献不易分离。通常采用非线性估计方法对不同部件的参数进行估计。这种非线性估计过程需要良好的起始值来快速和/或可靠地收敛到全局最小值。本文提出了一种仅根据一条测量记录计算第一次估计的方法。
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Wiener-Hammerstein System Estimator Initialisation Using a Random Multisine Excitation
Wiener-Hammerstein systems consist of a linear dynamic system followed by a static nonlinearity, followed by another linear dynamic system. These models are difficult to identify due to the presence of two dynamic systems whose contributions to the system behaviour aren¿t easily separable. Usually, a nonlinear estimation procedure is used to estimate the parameters of the different parts. This nonlinear estimation procedure needs good starting values to converge quickly and/or reliably to a global minimum. This paper proposes a method to compute a first estimate based on one measurement record only.
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