Robust identification with mixed parametric/nonparametric models and time/frequency-domain experiments: theory and an application
Robust identification with mixed parametric/nonparametric models and time/frequency-domain experiments: theory and an application
复制标题
混合参数/非参数模型和时/频域实验的鲁棒识别：理论与应用
DOI：
10.1109/cdc.1999.830920
复制
发表时间：
1999
期刊：
影响因子：
--
通讯作者：
R. Peña
中科院分区：
文献类型：
--
作者：
T. Inanc;M. Sznaier;P. Parrilo;R. Peña
Parillo等人。(1999)提出了一种基于广义内插理论的稳健辨识框架，该框架允许结合参数和非参数模型以及频率和时间域实验数据。我们通过一个两自由度结构的识别问题来说明该框架相对于传统的面向控制的识别技术的优势，该两自由度结构被用作展示损伤减轻和延长寿命控制概念的试验台。这种结构的阻尼性很差，导致了呈现大峰值的时域和频域响应，从而使识别问题变得非同小可。
Parillo et al. (1999) proposed a robust identification framework, based upon generalized interpolation theory, that allows for combining parametric and nonparametric models and frequency and time-domain experimental data. We illustrate the advantages of this framework over conventional control oriented identification techniques by considering the problem of identifying a two-degree of freedom structure used as a testbed for demonstrating damage-mitigation and life extension control concepts. This structure is poorly damped, leading to time and frequency domain responses that exhibit large peaks, thus rendering the identification problem non-trivial.