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Recursive Least Squares Algorithm for a Nonlinear Additive System with Time Delay 认领 引用
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作者 陈晶 王秀平 《Journal of Shanghai Jiaotong university(Science)》 EI 2016年第2期159-163,共5页
This paper proposes a recursive least squares algorithm for a nonlinear additive system with time delay.By the Weierstrass approximation theorem and the key term separation principle, the model can be simplified as an... This paper proposes a recursive least squares algorithm for a nonlinear additive system with time delay.By the Weierstrass approximation theorem and the key term separation principle, the model can be simplified as an identification model. Based on the identification model, a recursive least squares identification algorithm is used to estimate all the unknown parameters of the time-delayed additive system. An example is provided to show the effectiveness of the proposed algorithm. 展开更多
关键词 parameter estimation recursive least square algorithm Weierstrass approximation theorem key term separation principle additive system
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FAST RECURSIVE LEAST SQUARES LEARNING ALGORITHM FOR PRINCIPAL COMPONENT ANALYSIS 认领 引用 被引量：8
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作者 Ouyang Shan Bao Zheng Liao Guisheng 《Journal of Electronics(China)》 2000年第3期270-278,共9页
Based on the least-square minimization a computationally efficient learning algorithm for the Principal Component Analysis(PCA) is derived. The dual learning rate parameters are adaptively introduced to make the propo... Based on the least-square minimization a computationally efficient learning algorithm for the Principal Component Analysis(PCA) is derived. The dual learning rate parameters are adaptively introduced to make the proposed algorithm providing the capability of the fast convergence and high accuracy for extracting all the principal components. It is shown that all the information needed for PCA can be completely represented by the unnormalized weight vector which is updated based only on the corresponding neuron input-output product. The convergence performance of the proposed algorithm is briefly analyzed.The relation between Oja’s rule and the least squares learning rule is also established. Finally, a simulation example is given to illustrate the effectiveness of this algorithm for PCA. 展开更多
关键词 Neural networks Principal component analysis Auto-association Recursive least squares(RLS) learning rule
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CONVERGENCE AND STABILITY OF RECURSIVE DAMPED LEAST SQUARE ALGORITHM 认领 引用
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作者 陈增强 林茂琼 袁著祉 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2000年第2期237-242,共6页
The recursive least square is widely used in parameter identification. But if is easy to bring about the phenomena of parameters burst-off. A convergence analysis of a more stable identification algorithm-recursive da... The recursive least square is widely used in parameter identification. But if is easy to bring about the phenomena of parameters burst-off. A convergence analysis of a more stable identification algorithm-recursive damped least square is proposed. This is done by normalizing the measurement vector entering into the identification algorithm. rt is shown that the parametric distance converges to a zero mean random variable. It is also shown that under persistent excitation condition, the condition number of the adaptation gain matrix is bounded, and the variance of the parametric distance is bounded. 展开更多
关键词 system identification damped least square recursive algorithm convergence stability
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Recursive Least Squares Identification With Variable-Direction Forgetting via Oblique Projection Decomposition 认领 引用 被引量：7
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作者 Kun Zhu Chengpu Yu Yiming Wan 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2022年第3期547-555,共9页
In this paper,a new recursive least squares(RLS)identification algorithm with variable-direction forgetting(VDF)is proposed for multi-output systems.The objective is to enhance parameter estimation performance under n... In this paper,a new recursive least squares(RLS)identification algorithm with variable-direction forgetting(VDF)is proposed for multi-output systems.The objective is to enhance parameter estimation performance under non-persistent excitation.The proposed algorithm performs oblique projection decomposition of the information matrix,such that forgetting is applied only to directions where new information is received.Theoretical proofs show that even without persistent excitation,the information matrix remains lower and upper bounded,and the estimation error variance converges to be within a finite bound.Moreover,detailed analysis is made to compare with a recently reported VDF algorithm that exploits eigenvalue decomposition(VDF-ED).It is revealed that under non-persistent excitation,part of the forgotten subspace in the VDF-ED algorithm could discount old information without receiving new data,which could produce a more ill-conditioned information matrix than our proposed algorithm.Numerical simulation results demonstrate the efficacy and advantage of our proposed algorithm over this recent VDF-ED algorithm. 展开更多
关键词 Non-persistent excitation oblique projection recursive least squares(RLS) variable-direction forgetting(VDF)
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一个网络参数估计的增量式RLS算法 认领 引用
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作者 王忠禹 冶继民 《吉林大学学报（理学版）》 CAS 北大核心 2026年第3期643-649,共7页
针对现有增量式最小均方算法仅利用各节点的局部数据进行局部估计,在信息交互受限条件下估计精度较低的问题,提出一种循环网络估计的增量式递归最小二乘算法.该算法在循环网络中逐节点对局部损失函数进行指数加权求和,仅利用前一节点参... 针对现有增量式最小均方算法仅利用各节点的局部数据进行局部估计,在信息交互受限条件下估计精度较低的问题,提出一种循环网络估计的增量式递归最小二乘算法.该算法在循环网络中逐节点对局部损失函数进行指数加权求和,仅利用前一节点参数的局部估计值和中间过程矩阵的估计值,递归求解每个节点处的局部估计,具有信息交互需求低、估计精度高的特点.通过对该估计方法的均值和均方误差理论分析可知,仿真实验结果与理论分析高度吻合.在不同应用场景下,该算法估计精度均优于目前对比增量式最小均方算法,为分布式循环网络中的参数估计提供了一种高效可行的解决方案. 展开更多
关键词 自适应算法 增量形式 递归最小二乘
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Prediction of Time Series Empowered with a Novel SREKRLS Algorithm 认领 引用 被引量：3
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作者 Bilal Shoaib Yasir Javed +6 位作者 Muhammad Adnan Khan Fahad Ahmad Rizwan Majeed Muhammad Saqib Nawaz Muhammad Adeel Ashraf Abid Iqbal Muhammad Idrees 《Computers, Materials & Continua》 SCIE EI 2021年第5期1413-1427,共15页
For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article.The proposed algorithm lends itself ... For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article.The proposed algorithm lends itself towards the parallel implementation as in the FPGA systems.With the help of an ortho-normal triangularization method,which relies on numerically stable givens rotation,matrix inversion causes a computational burden,is reduced.Matrix computation possesses many excellent numerical properties such as singularity,symmetry,skew symmetry,and triangularity is achieved by using this algorithm.The proposed method is validated for the prediction of stationary and non-stationary Mackey–Glass Time Series,along with that a component in the x-direction of the Lorenz Times Series is also predicted to illustrate its usefulness.By the learning curves regarding mean square error(MSE)are witnessed for demonstration with prediction performance of the proposed algorithm from where it’s concluded that the proposed algorithm performs better than EKRLS.This new SREKRLS based design positively offers an innovative era towards non-linear systolic arrays,which is efficient in developing very-large-scale integration(VLSI)applications with non-linear input data.Multiple experiments are carried out to validate the reliability,effectiveness,and applicability of the proposed algorithm and with different noise levels compared to the Extended kernel recursive least-squares(EKRLS)algorithm. 展开更多
关键词 Kernel methods square root adaptive filtering givens rotation mackey glass time series prediction recursive least squares kernel recursive least squares extended kernel recursive least squares square root extended kernel recursive least squares algorithm
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Analysis and implementation of FURLS algorithm for active vibration control system with positive feedback 认领 引用
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作者 高志远 Zhu Xiaojin +2 位作者 Zhang Hesheng Luo Cong Li Mingdong 《High Technology Letters》 EI CAS 2015年第2期171-177,共7页
While positive feedback exists in an active vibration control system, it may cause instability of the whole system. To solve this problem, a feedforward adaptive controller is proposed based on the Fihered-U recursive... While positive feedback exists in an active vibration control system, it may cause instability of the whole system. To solve this problem, a feedforward adaptive controller is proposed based on the Fihered-U recursive least square （FURLS） algorithm. Algorithm development process is presented in this paper. Real time active vibration control experimental tests were done. The experiment resuits show that the active control algorithm proposed in this paper has good control performance for both narrow band disturbances and broad band disturbances. 展开更多
关键词 adaptive control active vibration control Filtered-U recursive least square（FURLS） algorithm
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基于IFFRLS-IMMUKF的商用车磷酸铁锂电池SOC估算 认领 引用 被引量：4
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作者 吴华伟 何成泽 +3 位作者 洪强 周小高 李明金 顾亚娟 《储能科学与技术》 CAS CSCD 北大核心 2025年第10期3996-4008,共13页
荷电状态(SOC)作为电动汽车剩余容量的表征参数,它的准确预估可以保障电动汽车的安全可靠性。针对复杂环境下电池SOC难以精确估算的问题,本工作基于动力电池特性构建了等效电路模型,并对电池模型状态方程进行了离散化的推演,在获得离散... 荷电状态(SOC)作为电动汽车剩余容量的表征参数,它的准确预估可以保障电动汽车的安全可靠性。针对复杂环境下电池SOC难以精确估算的问题,本工作基于动力电池特性构建了等效电路模型,并对电池模型状态方程进行了离散化的推演,在获得离散化状态方程的基础上,将金豺优化算法与遗忘因子递推最小二乘法(FFRLS)相结合提出了改进遗忘递推最小二乘法对电池模型进行了参数辨识。同时,联合交互式多模型无迹卡尔曼滤波(IMMUKF)算法对电池SOC进行估算,并在对常温和高温条件下的动态应力(DST)和联邦城市驾驶工况(FUDS)进行试验验证。结果表明,基于IFFRLS-IMMUKF的锂电池SOC估算方法,其平均绝对值误差在0.8%之内,对磷酸铁锂电池有较高的SOC估算精度。 展开更多
关键词 金豺优化算法 遗忘因子递推最小二乘法 交互式多模型无迹卡尔曼滤波 荷电状态
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Blind cancellation for frequency offset in OFDM system based on MCMA-RLS algorithm 认领 引用
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作者 Guan Qingyang Zhao Honglin Guo Qing 《High Technology Letters》 EI CAS 2011年第4期366-370,共5页
Modified constant modulus and recursive least squares （MCMA-RLS） algorithm is proposed to cancel interference caused by the variable frequency offset （FO） in the orthogonal frequency division multiplexing （OFDM）... Modified constant modulus and recursive least squares （MCMA-RLS） algorithm is proposed to cancel interference caused by the variable frequency offset （FO） in the orthogonal frequency division multiplexing （OFDM） system. The MCMA-RLS algorithm is composed of two stages including MCMA scheme and RLS scheme. MCMA is selected to pre-cancel the variable frequency offset firstly, and then the residual interference has been canceled by the RLS scheme. BR error rate is simulated to demonstrate that the proposed method is robust for canceling the variable frequency offset. 展开更多
关键词 orthogonal frequency division multiplexing （OFDM） fxequency offset （FO） modified constantmodulus algorithm （MCMA） reeursive least squares （RLS）
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Multi-loop adaptive internal model control based on a dynamic partial least squares model 认领 引用 被引量：4
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作者 Zhao ZHAO Bin HU Jun LIANG 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2011年第3期190-200,共11页
A multi-loop adaptive internal model control(IMC)strategy based on a dynamic partial least squares(PLS)frame-work is proposed to account for plant model errors caused by slow aging,drift in operational conditions,or e... A multi-loop adaptive internal model control(IMC)strategy based on a dynamic partial least squares(PLS)frame-work is proposed to account for plant model errors caused by slow aging,drift in operational conditions,or environmental changes.Since PLS decomposition structure enables multi-loop controller design within latent spaces,a multivariable adaptive control scheme can be converted easily into several independent univariable control loops in the PLS space.In each latent subspace,once the model error exceeds a specific threshold,online adaptation rules are implemented separately to correct the plant model mismatch via a recursive least squares(RLS)algorithm.Because the IMC extracts the inverse of the minimum part of the internal model as its structure,the IMC controller is self-tuned by explicitly updating the parameters,which are parts of the internal model.Both parameter convergence and system stability are briefly analyzed,and proved to be effective.Finally,the proposed control scheme is tested and evaluated using a widely-used benchmark of a multi-input multi-output(MIMO)system with pure delay. 展开更多
关键词 Partial least squares(PLS) Adaptive internal model control(IMC) Recursive least squares(RLS)
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基于RLS-RBPF算法的车辆悬架参数辨识方法研究 认领 引用
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作者 王姝 董传昊 +3 位作者 张大伟 赵轩 周辰雨 邵帅 《重庆理工大学学报（自然科学）》 CAS 北大核心 2025年第7期19-27,共9页
在汽车的运行过程中,悬架系统的状态不可避免地会发生改变。为了准确评估悬架参数的长期变化,尤其是实现早期故障预警,提出了一种基于车辆实际行驶状态的悬架参数辨识方法,首先在车辆的关键部位安装振动传感器,采集振动加速度信号。然后... 在汽车的运行过程中,悬架系统的状态不可避免地会发生改变。为了准确评估悬架参数的长期变化,尤其是实现早期故障预警,提出了一种基于车辆实际行驶状态的悬架参数辨识方法,首先在车辆的关键部位安装振动传感器,采集振动加速度信号。然后,通过递推最小二乘算法对悬架的弹簧刚度和减震器阻尼系数进行初步识别。在此基础上,进一步采用Rao-Blackwellized粒子滤波算法对初步辨识结果进行二次优化。最后,结合实测的车辆硬点坐标和通过辨识得到的悬架参数,基于多体动力学原理构建车辆动力学模型,与实际设计参数进行对比,并进行整车动力学仿真以验证辨识参数的准确性。实验结果表明,该方法在识别悬架弹簧刚度和减震器阻尼系数方面具有很高的精度,与真实值的最大偏差仅为2.50%和1.82%。同时,车辆动力学模型的仿真输出与实测载荷谱的均方根误差控制在5%以内。该方法显著提高了悬架系统参数辨识的精确度,是一种高精度的汽车悬架参数在线辨识算法。 展开更多
关键词 递推最小二乘算法 RBPF算法 实车载荷谱 参数辨识
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基于STD-RLS自适应算法的微震波工频干扰消除方法研究 认领 引用 被引量：1
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作者 刘宝霖 张明伟 +1 位作者 袁国涛 田壮才 《大地测量与地球动力学》 CSCD 北大核心 2025年第9期954-963,共10页
提出一种结合时间序列季节趋势离散(seasonal trend dispersion,STD)分解和递推最小二乘(recursive least squares,RLS)法的自适应去除工频干扰方法。该方法利用STD分解提取含工频干扰微震波的季节项,作为RLS的参考信号,并动态更新算法... 提出一种结合时间序列季节趋势离散(seasonal trend dispersion,STD)分解和递推最小二乘(recursive least squares,RLS)法的自适应去除工频干扰方法。该方法利用STD分解提取含工频干扰微震波的季节项,作为RLS的参考信号,并动态更新算法系数,使计算信号接近工频干扰信号。设计仿真实验,将1组无工频干扰的微震波与3种不同类型工频干扰叠加,分别使用有限冲击响应(finite impulse response,FIR)滤波、小波阈值(wavelet threshold,WT)滤波和本文方法进行处理。结果表明,本文方法能有效去除工频干扰,同时完整保留微震波的关键时频特征。此外,将本文方法应用于桃园煤矿微震监测数据处理,验证了其工程应用的可行性与可靠性。 展开更多
关键词 微震波 工频干扰 季节趋势离散分解 递推最小二乘法 自适应算法
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A RESEARCH OF UWB RAKE RECEIVER BASED ON NOVEL RLS ADAPTIVE ALGORITHM 认领 引用 被引量：2
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作者 Yin Yong Yu Nenghai Dong Weijie 《Journal of Electronics(China)》 2006年第3期341-345,共5页
A modified RAKE receiver based on novel Recursive Least Squares （RLS） adaptive algorithm is proposed. The receiver uses L-fingered correlators, which are composed of RLS adaptive filters, to enhance the performance ... A modified RAKE receiver based on novel Recursive Least Squares （RLS） adaptive algorithm is proposed. The receiver uses L-fingered correlators, which are composed of RLS adaptive filters, to enhance the performance of multipath receiving. It can also track the amplitude of the received signal to form a real-time amplitude estimation which is correlated with the power of excess delay bin. The simulation results based on the IEEE UltraWide Band （UWB） channel models （CMI to CM4） show that the novel RLS algorithm can alter the attenuation estimation with the finger＇s power delay profile, and RAKE receiver with few fingers can be employed to get high performance. 展开更多
关键词 UltraWide Band （UWB） RAKE receiver Recursive Least Squares （RLS）
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一种基于RLS估计的多位置初始对准算法 认领 引用 被引量：1
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作者 肖宇圻 李智 《航天控制》 CSCD 2025年第3期66-75,共10页
针对航空航天载具所搭载的旋转调制惯性导航系统在冷启动时难以短时间内实现精确初始对准的问题,提出一种基于递推最小二乘(RLS)且采用多位置对准的全新对准方法:该方法以惯导系统速度误差分析为依据,推导误差速度与姿态失准角以及惯性... 针对航空航天载具所搭载的旋转调制惯性导航系统在冷启动时难以短时间内实现精确初始对准的问题,提出一种基于递推最小二乘(RLS)且采用多位置对准的全新对准方法:该方法以惯导系统速度误差分析为依据,推导误差速度与姿态失准角以及惯性测量单元零偏的关联方程,实现惯导系统的误差修正;运用RLS估计和迭代优化,解析出初始目标对准误差参数;通过仿真实验和实物实验进行验证。结果表明,在短时间内冷启动的情况下,该方法相较于传统卡尔曼滤波对准算法,能够达到显著提升惯导系统方位角的初始对准精度的效果,使惯导系统在各方位下对准所得方位角的均方根误差平均减少约42.7%。 展开更多
关键词 初始对准算法 递推最小二乘 惯导系统 多位置对准 迭代优化 冷启动
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TPC-BASED STBC MULTIUSER DETECTION WITH LSE-RLS ALGORITHM 认领 引用
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作者 Du Yinggang Chan Kam Tai 《Journal of Electronics(China)》 2006年第1期23-25,共3页
The Bit Error Rate （BER） performance of a Turbo Product Code （TPC） based Space-Time Block Coding （STBC） multiuser wireless system in the frequency-selective channels has been investigated. Both of the good error... The Bit Error Rate （BER） performance of a Turbo Product Code （TPC） based Space-Time Block Coding （STBC） multiuser wireless system in the frequency-selective channels has been investigated. Both of the good error correcting capability of TPC and the large diversity gain of STBC can be achieved simultaneously. A Least Square Error-Recursive Least Square （LSE-RLS） algorithm is applied to estimate the channel and cancel the interference. Simulations show that the proposed system can obtain about 2.7dB gain in Es/N0 at the BER of 10^-3. 展开更多
关键词 Turbo Product Code （TPC） Space-Time Block Coding （STBC） Multiuser Least Square Error（LSE） Recursive Least Square （RLS）
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轮式拖拉机电机驱动导航转向系统参数辨识方法 认领 引用
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作者 张健 邵珠和 +3 位作者 李耀 潘志国 张还 孙良庆 《农业机械学报》 EI CAS CSCD 北大核心 2026年第9期105-115,共11页
农业机械导航系统应用日益广泛,但在地形起伏大、作业环境恶劣及作物类型复杂的工况,如热带区、丘陵地区,会显著降低导航系统的路径跟踪精度与鲁棒性。转向系统是农机导航系统的核心部件,精准的转向控制是实现高精度路径跟踪的前提。获... 农业机械导航系统应用日益广泛,但在地形起伏大、作业环境恶劣及作物类型复杂的工况,如热带区、丘陵地区,会显著降低导航系统的路径跟踪精度与鲁棒性。转向系统是农机导航系统的核心部件,精准的转向控制是实现高精度路径跟踪的前提。获取准确的转向系统数学模型可有效降低转向控制算法的设计难度与复杂性。然而,由于转向系统中存在动态滞后、非线性摩擦、死区效应及环境相关扰动等未建模动态,采用机理分析方法难以建立准确的转向系统数学模型。为此,本文提出了一种基于卡尔曼滤波(KF)与带正则项递归最小二乘法(RRLS)联合辨识的转向系统建模方法。在Matlab环境下搭建辨识平台,分别实现并比较RLS、KF+RLS与KF+RRLS 3种辨识方案的仿真结果,筛选出性能最优的模型为KF+RRLS。随后开展田间复杂工况验证试验,结果表明:所辨识模型对轮角响应的轨迹预测与实测数据的吻合程度为95.26%,关键动态特性被可靠复现,且满足实时性要求。该模型为复杂环境下农机导航系统的路径跟踪控制算法设计提供了可靠的模型基础与工程化支撑。 展开更多
关键词 轮式拖拉机 导航转向系统 系统参数辨识 卡尔曼滤波 正则递归最小二乘算法
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基于改进多新息最小二乘算法的锂电池参数辨识研究 认领 引用
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作者 宋维华 刘冉冉 +2 位作者 金晓娜 孙志英 姜学艳 《现代电子技术》 北大核心 2026年第4期126-134,共9页
锂离子电池作为电动汽车的主要动力来源,凭借能量密度高、循环寿命长等优势而得到广泛使用。但汽车的运行工况复杂,导致锂离子电池荷电状态(SOC)难以准确估计。而在SOC估计研究中,准确的模型参数可提高SOC的估计精度。为此,设计了改进... 锂离子电池作为电动汽车的主要动力来源,凭借能量密度高、循环寿命长等优势而得到广泛使用。但汽车的运行工况复杂,导致锂离子电池荷电状态(SOC)难以准确估计。而在SOC估计研究中,准确的模型参数可提高SOC的估计精度。为此,设计了改进自适应遗忘因子(IAFF)调节机制,并提出一种改进自适应遗忘因子多新息递推最小二乘(IAFFMIRLS)算法。该算法不仅能够提高参数辨识的准确性,而且在抗干扰能力上具有优异的性能。仿真验证结果表明,相比可变遗忘因子递推最小二乘(VFFRLS)算法、自适应遗忘因子递推最小二乘(AFFRLS)算法与多新息最小二乘(MIRLS)算法,IAFFMIRLS算法的均方根误差(RMSE)分别降低了97.06%、91.40%和72.02%,在噪声干扰下辨识的RMSE分别降低了97.24%、62.55%和83.13%,验证了该算法具有较高的辨识精度和抗干扰性,能够为提升电池状态估计与寿命预测的可靠性提供理论支撑。 展开更多
关键词 锂离子电池 参数辨识 荷电状态 自适应遗忘因子 多新息递推最小二乘算法 等效电路模型
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采用改进递归最小二乘法的电动负载模拟器参数在线辨识 认领 引用 被引量：1
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作者 夏玉香 李成成 李跃峰 《机械科学与技术》 CSCD 北大核心 2026年第3期548-556,共9页
针对电动负载模拟器在线参数辨识过程中传感器噪声及较小的遗忘因子可能导致的辨识过程不收敛问题,该文通过在传统最小二乘算法中引入低通滤波器和协方差矩阵重调,提出了一种改进的带遗忘因子递归最小二乘在线参数辨识方法(IFRLS)。首先... 针对电动负载模拟器在线参数辨识过程中传感器噪声及较小的遗忘因子可能导致的辨识过程不收敛问题,该文通过在传统最小二乘算法中引入低通滤波器和协方差矩阵重调,提出了一种改进的带遗忘因子递归最小二乘在线参数辨识方法(IFRLS)。首先,建立了电动负载模拟器的加载数学模型,设计了辨识过程中的滤波方法。其次,在传统带遗忘因子最小二乘算法的基础上引入协方差重调,解决了辨识结果不收敛问题。最后,进行在线参数辨识实验和辨识准确性验证实验。实验结果表明:该方法解决了辨识过程不收敛问题,并实现了电动负载模拟器全部参数的在线辨识,得到的辨识模型与真实模型的拟合度达到93.8%。 展开更多
关键词 电动负载模拟器 改进递归最小二乘法 参数辨识 协方差矩阵
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基于改进RLS算法的故障电流参数估计 认领 引用 被引量：26
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作者 黄智慧 段雄英 +1 位作者 邹积岩 万慧明 《中国电机工程学报》 EI CSCD 北大核心 2014年第15期2460-2469,共10页
由于故障电流中直流衰减分量的影响,快速准确地估计出故障电流参数并预测出可用的过零点成为故障电流相控开断的关键。将故障电流方程中指数项进行泰勒级数展开,保留前2项,并基于递推最小二乘法,估计电流参数。分析由泰勒级数展开引起... 由于故障电流中直流衰减分量的影响,快速准确地估计出故障电流参数并预测出可用的过零点成为故障电流相控开断的关键。将故障电流方程中指数项进行泰勒级数展开,保留前2项,并基于递推最小二乘法,估计电流参数。分析由泰勒级数展开引起的截断误差,提出时间常数补偿公式。利用Matlab软件对不含谐波和含有谐波两种情况下的故障进行仿真,结果表明:算法可在15 ms内得到足够精度的故障电流参数,电流过零点的预测精度在?0.2 ms以内。最后对故障录波数据的仿真结果证实了算法的效果。 展开更多
关键词 故障电流相控开断 递推最小二乘法 参数估计 过零点预测
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Application of RLS adaptive filteringin signal de-noising 认领 引用 被引量：8
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作者 程学珍 徐景东 +1 位作者 卫阿盈 逄明祥 《Journal of Measurement Science and Instrumentation》 CAS 2014年第1期32-36,共5页
In view of the problem that noises are prone to be mixed in the signals,an adaptive signal de-noising system based on reursive least squares （RLS） algorithm is introduced.The principle of adaptive filtering and the ... In view of the problem that noises are prone to be mixed in the signals,an adaptive signal de-noising system based on reursive least squares （RLS） algorithm is introduced.The principle of adaptive filtering and the process flow of RLS algorithm are described.Through example simulation,simulation figures of the adaptive de-noising system are obtained.By analysis and comparison,it can be proved that RLS adaptive filtering is capable of eliminating the noises and obtaining useful signals in a relatively good manner.Therefore,the validity of this method and the rationality of this system are demonstrated. 展开更多
关键词 de-noising adaptive filtering recursive least squares （RLS） algorithm
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