Least Squares Based Iterative Parameter Estimation Algorithm for State Space Model with Time-Delay

Gu Ya, Chou Yongxin, Ding Wei, L. Jicheng
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Abstract

This paper researches parameter estimation problem for state space systems with time-delay. Combing the linear transformation and the property of the shift operator, the state space model with time-delay can be equivalent to the input-output representation and then can be transformed into the identification model. The least squares based iterative parameter estimation algorithm is raised to identify the system with time-delay and makes full use of all data at each iteration and thus can generate highly accurate parameter estimates. Finally, the example is provided to validate the proposed theorems.
基于最小二乘的时滞状态空间模型迭代参数估计算法
研究了具有时滞的状态空间系统的参数估计问题。结合线性变换和位移算子的性质,将时滞状态空间模型等效为输入-输出表示,进而转化为识别模型。提出了基于最小二乘的迭代参数估计算法来识别具有时滞的系统,并充分利用每次迭代的所有数据,从而产生高精度的参数估计。最后,通过算例验证了所提定理的正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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