A New Least Squares Iterative Estimation Algorithm for CARAR Systems

Lijuan Wan, Chunping Chen, Yan Ji
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引用次数: 1

Abstract

Mathematical models are the base for the system analysis and the controller design. This paper focuses on the identification problems of controlled autoregressive models with autoregressive noise (CARAR system for short). By applying the iterative method and the hierarchical principle, a least squares identification algorithm is investigated. The key of this algorithm is replacing the unknown noise terms in the information vector with their estimated residuals. The effectiveness of this approach is demonstrated by the simulation experiment.
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CARAR系统的一种新的最小二乘迭代估计算法
数学模型是系统分析和控制器设计的基础。本文主要研究带自回归噪声的可控自回归模型(简称CARAR系统)的辨识问题。应用迭代法和分层原理,研究了一种最小二乘辨识算法。该算法的关键是将信息向量中的未知噪声项替换为其估计残差。仿真实验验证了该方法的有效性。
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