CLC number: O231
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2019-09-06
Cited: 0
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Mitar Simić, Zdenka Babić, Vladimir Risojević, Goran M. Stojanović. Non-iterative parameter estimation of the 2R-1C model suitable for low-cost embedded hardware[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.1900112 @article{title="Non-iterative parameter estimation of the 2R-1C model suitable for low-cost embedded hardware", %0 Journal Article TY - JOUR
适于低成本嵌入式硬件的2R-1C模型非迭代参数估计1巴尼亚卢卡大学电气工程学院,波黑巴尼亚卢卡,78000 2诺维萨德大学技术科学学院,塞尔维亚共和国诺维萨德,21000 摘要:2R-1C模型的参数估计常运用需要高性能处理单元的迭代方法,从而激励我们研究更省时且更节能的参数估计方法。这些低复杂度的算法将更适于便携式微机设备的运行。本文提出二次插值非迭代参数估计方法(QINIPE);该方法基于测量阻抗虚部的二次插值,能够更精确地估计特征频率。运用一组封闭表达式从测量阻抗的实部和虚部计算2R-1C模型的参数。对仿真和测量获得的模型阻抗数据作对比分析;结果表明,相较于我们早前提出的非迭代参数估计方法(NIPE),QINIPE能减少80%测量点,且所有估计参数的相对估计误差低于1%。两种非迭代方法均基于一个微机设备实施;检测了估计精度、RAM、闪存使用以及运行时间。实验结果表明,相较于NIPE,QINIPE轻微增加了0.576ms运行时间(约6.7%),且需要多24%(1.2KB)闪存及多2.4%(32字节)RAM。然而,QINIPE的阻抗均方根误差分别降低至NIPE对应的42.8%(实部)和64.5%(虚部)。此外,比较了QINIPE和复杂非线性最小二乘法(CNLS)对2R-1C模型参数的估计。结果表明,虽然QINIPE估计精度稍低于CNLS,其依然适合许多实际应用,且运行时间降至原来的1/45至1/30。 关键词组: Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article
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