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基于辅助模型思想的带可变遗忘因子的最小二乘辨识算法

Recursive Least Square Method Based on Auxiliary Model with a Variable Forgetting Factor
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摘要 为了对时滞系统的时滞参数和系统动态参数进行辨识,本文提出了一种基于辅助模型思想的带可变遗忘因子的最小二乘辨识算法。建立辅助模型,用辅助模型输出代替系统的无噪声输出。引入基于预测误差的可变遗忘因子,加快算法的收敛速度,提高算法的预测精度。最后,通过仿真证明了本文算法的有效性。 In order to identify the time-delay and dynamic parameters, recursive least square method based on auxihary model(AM) with a variable forgetting factor(VFF) is proposed. An auxiliary model (AM) is established to estimate the noise-free output of system. A variable forgetting factor (VFF) based on prediction error is introduced to enhance the convergence rate and identification accuracy. Simulation results are included to show the effectiveness of this method.
出处 《北华航天工业学院学报》 CAS 2016年第3期17-19,28,共4页 Journal of North China Institute of Aerospace Engineering
基金 北华航天工业学院基金(KY-2015-05) 北华航天工业学院基金(KY-2014-01) 廊坊市科技支撑计划项目(2015011044) 河北省高等学校科学技术研究项目(QN2015103)
关键词 时滞 最小二乘 辅助模型 可变遗忘因子 time-delay, least square, auxiliary model (AM), variable forgetting factor (VFF)
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参考文献6

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