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Bias compensation-based parameter estimation for output error moving average systems

机译:输出误差移动平均系统基于偏差补偿的参数估计

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摘要

Identification problems of output error models with moving average noises are considered in this paper. The least-squares-based parameter estimation is biased under the colored noises in outputs. Firstly, a bias compensation term is formulated to achieve the bias-eliminated estimates of the system parameters. Secondly, the bias compensation term is determined by the unknown variance of the noise and the unknown noise model, thus based on the hierarchical identification principle, an unbiased parameter estimation is obtained by interactively estimating noise variance and noise parameters. Finally, the estimated bias compensation term is added to the biased parameter estimates. The simulation examples confirm the effectiveness of the proposed algorithm.
机译:本文考虑了带有移动平均噪声的输出误差模型的辨识问题。基于最小二乘的参数估计在输出中的有色噪声下有偏差。首先,制定偏置补偿项以实现系统参数的偏置消除估计。其次,由噪声的未知方差和未知噪声模型确定偏差补偿项,从而基于层次识别原理,通过交互估计噪声方差和噪声参数来获得无偏参数估计。最后,将估计的偏置补偿项添加到偏置参数估计中。仿真算例验证了所提算法的有效性。

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