Parametric identification of closed-loop linear systems using cyclic-spectral analysis
Parametric identification of closed-loop linear systems using cyclic-spectral analysis
复制标题
使用循环谱分析对闭环线性系统进行参数辨识
DOI：
--
复制
发表时间：
1998
期刊：
影响因子：
--
通讯作者：
Jitendra Tugnait
中科院分区：
文献类型：
--
作者：
C. Tontiruttananon;Jitendra Tugnait
考虑了给定噪声时域输入输出测量的闭环系统辨识问题。它是假设影响系统的各种干扰是零均值平稳的，而闭环系统的外部循环平稳输入下，这是不测量操作。假设工厂的（直接）输入和输出的噪声测量是可用的。闭环系统必须是稳定的，但允许开环系统是不稳定的。提出了两种新的辨识算法，利用循环谱分析的噪声输入输出数据。对于这两种方法，开环传递函数首先估计使用的输入输出数据的循环谱和循环互谱。这些传递函数的估计，然后被用作“数据”所提出的算法。这两类参数估计是弱一致的任何平稳和一类循环平稳噪声（无论是在输入和输出）。计算机模拟的例子中提出的方法支持。
The problem of closed-loop system identification given noisy time-domain input-output measurements is considered. It is assumed that the various disturbances affecting the system are zero-mean stationary whereas the closed-loop system operates under an external cyclostationary input which is not measured. Noisy measurements of the (direct) input and output of the plant are assumed to be available. The closed-loop system must be stable but it is allowed to be unstable in open-loop. Two new identification algorithms are proposed using cyclic-spectral analysis of noisy input-output data. For both approaches, the open-loop transfer function is first estimated using the cyclic-spectrum and cyclic cross-spectrum of the input-output data. These transfer function estimates are then used as "data" for the proposed algorithms. Both classes of parameter estimators are shown to be weakly consistent in any stationary and a class of cyclostationary noise (both at input as well as output). Computer simulation examples are presented in support of the proposed approaches.