Mixed time/frequency-domain based robust identification
Mixed time/frequency-domain based robust identification
复制标题
基于混合时域/频域的鲁棒识别
DOI：
10.1109/cdc.1996.577444
复制
发表时间：
1998
期刊：
影响因子：
--
通讯作者：
T. Inanc
中科院分区：
文献类型：
--
作者：
P. Parrilo;M. Sznaier;R. Peña;T. Inanc
在本文中，我们提出了一个新的鲁棒识别框架，结合频域和时域的实验数据。本文的主要结果表明，建立数据的一致性和获得一个标称模型和界的识别误差的问题可以被改写为一个约束有限维凸优化问题，可以有效地解决使用线性矩阵不等式技术。这种方法，根据广义插值理论，包含作为特殊情况下的Caratheodory-Fejer（纯时域）和Nevanlinna-Pick（纯频域）的问题。所提出的程序内插的频率和时域的实验数据，同时限制所识别的系统是在一个先验的给定类的模型，从而在一个标称模型与两个数据源一致。因此，它是收敛的和最佳的2倍（相对于中央算法）。
In this paper we propose a new robust identification framework that combines both frequency and time-domain experimental data. The main result of the paper shows that the problems of establishing consistency of the data and of obtaining a nominal model and bounds on the identification error can be recast as a constrained finite-dimensional convex optimisation problem that can be efficiently solved using linear matrix inequalities techniques. This approach, based upon a generalised interpolation theory, contains as special cases the Caratheodory-Fejer (purely time-domain) and Nevanlinna-Pick (purely frequency-domain) problems. The proposed procedure interpolates the frequency and time domain experimental data while restricting the identified system to be in an a priori given class of models, resulting in a nominal model consistent with both sources of data. Thus, it is convergent and optimal up to a factor of 2 (with respect to central algorithms).