论文标题
带有周期性输入的线性时间周期系统的子空间识别
Subspace Identification of Linear Time-Periodic Systems with Periodic Inputs
论文作者
论文摘要
本文提出了一种新方法，用于识别具有周期性输入的线性时间周期（LTP）系统。该方法通过使用线性时间不变结构利用时间段系统的频率响应来克服与LTP系统频率响应相关的问题。响应是通过带有周期性输入的输入输出数据集合来估计的。这允许频域子空间识别技术扩展到LTP系统。然后可以估算时间偏置的周期性脉冲响应，并制定块 - 烷基矩阵的订单浏览分解。在轻度噪声假设下证明了该方法的一致性。数值模拟表明，当有周期性数据合奏时，所提出的方法的性能优于多个广泛使用的时间域子空间识别方法。
This paper proposes a new methodology for subspace identification of linear time-periodic (LTP) systems with periodic inputs. This method overcomes the issues related to the computation of frequency response of LTP systems by utilizing the frequency response of the time-lifted system with linear time-invariant structure instead. The response is estimated with an ensemble of input-output data with periodic inputs. This allows the frequency-domain subspace identification technique to be extended to LTP systems. The time-aliased periodic impulse response can then be estimated and the order-revealing decomposition of the block-Hankel matrix is formulated. The consistency of the proposed method is proved under mild noise assumptions. Numerical simulation shows that the proposed method performs better than multiple widely-used time-domain subspace identification methods when an ensemble of periodic data is available.
