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A modified recurrent least squares algorithm for online closed-loop identification for processes with time delay

机译:时滞过程在线闭环辨识的改进递推最小二乘算法

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Focuses on an algorithm of linear digital dynamic models online identification based on recurrent parameter estimation for processes with time delay. This algorithm is efficient for adaptive control systems design. The delay of the linear part of a digital model in the S-domain is estimated as well as parameters of a numerator and denominator of a transfer function (TF) in the Z-domain. This allows us to correct the delay of a model in the Z-domain and accordingly to make a correction of the recurrent least squares algorithm. The experimental results of prop-fan engine identification are submitted. The algorithm can also be useful for checking of process model structure correctness and choosing of an optimum interval of time discretisation in digital control system design.
机译:着重研究一种基于递归参数估计的线性数字动态模型在线辨识算法,该过程具有时延。该算法对于自适应控制系统设计是有效的。估计数字模型的线性部分在S域中的延迟以及Z域中传递函数(TF)的分子和分母的参数。这使我们可以校正模型在Z域中的延迟,并因此可以对递归最小二乘算法进行校正。提交了风扇发动机识别的实验结果。该算法还可用于检查过程模型结构的正确性以及在数字控制系统设计中选择最佳时间离散化时间间隔。

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