A polynomial model, time origin shifting model(TOSM, is used to describe the trajectory of a moving target .Based on TOSM, a recursive laeast squares(RLS) algorithm with varied forgetting factor is derived for tracki...A polynomial model, time origin shifting model(TOSM, is used to describe the trajectory of a moving target .Based on TOSM, a recursive laeast squares(RLS) algorithm with varied forgetting factor is derived for tracking of a non-maneuvering target. In order to apply this algorithm to maneuvering targets tracking ,a tracking signal is performed on-line to determine what kind of TOSm will be in effect to track a target with different dynamics. An effective multiple model least squares filtering and forecasting method dadpted to real tracking of a maneuvering target is formulated. The algorithm is computationally more effcient than Kalman filter and the percentage improvement from simulations show both of them are considerably alike to some extent.展开更多
Considering that channel estimation plays a crucial role in coherent detection, this paper addresses a method of Recursive-least-squares (RLS) channel estimation with adaptive forgetting factor in wireless space-time ...Considering that channel estimation plays a crucial role in coherent detection, this paper addresses a method of Recursive-least-squares (RLS) channel estimation with adaptive forgetting factor in wireless space-time coded multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Because there are three different forgetting factor scenarios including adaptive, two-step and conventional ones applied to RLS channel estimation, this paper describes the principle of RLS channel estimation and analyzes the impact of different forgetting factor scenarios on the performances of RLS channel estimation. Simulation results proved that the RLS algorithm with adaptive forgetting factor (RLS-A) outperformed that with two-step forgetting factor (RLS-T) or with conventional forgetting factor (RLS-C) in both estimation accuracy and robustness over the multiple-input multiple-output (MIMO) channel, i.e., a wide-sense stationary uncorrelated scattering (WSSUS) and frequency-selective slowly fading channel. Hence, we can employ the RLS-A method by adjusting forgetting factor adaptively to track and estimate channel state parameters successfully in space-time coded MIMO-OFDM systems.展开更多
针对多种电机采用的控制器模型也存在不同,电机参数存在多样性,并且针对多种工况下,电机在工作过程中存在参数变化、负载扰动等情况,导致电机参数辨识精度不高、电机-控制器模型失配等问题,提出了一种改进递归最小二乘法(recursive leas...针对多种电机采用的控制器模型也存在不同,电机参数存在多样性,并且针对多种工况下,电机在工作过程中存在参数变化、负载扰动等情况,导致电机参数辨识精度不高、电机-控制器模型失配等问题,提出了一种改进递归最小二乘法(recursive least squares,RLS)算法进行多种工况下多电机参数失配诊断。针对传统的递归最小二乘法在进行在线电机参数辨识时,容易固遗忘因子影响,存在跟随速度慢、抗干扰性差等问题,在原始递归最小二乘法基础上引入了随系统工况变化而变化的“变遗忘因子”,提高电机参数的跟踪速度和抗负载扰动能力;为验证改进后的递归最小二乘法是否具有可靠性、鲁棒性和泛化性,分别设置了5种假设工况,并进行多组实验对比,通过分析电机速度响应、d-q轴电流以及量化分析转矩跟踪和R_(s)参数辨识精度等,验证改进后的算法具有较强的鲁棒性和泛化性;并通过分析性能指标数据,主要包括平均速度、平均q轴电流等,得出改进后算法分析数据的有效性。展开更多
荷电状态(state of charge,SOC)的准确估计对延长电池寿命、减少事故发生至关重要。针对锂电池系统存在建模误差及宽温度范围下传统方法适应性差的问题,设计一种自适应增益滑模观测器(adaptive gain sliding mode observer,AGSMO)以提...荷电状态(state of charge,SOC)的准确估计对延长电池寿命、减少事故发生至关重要。针对锂电池系统存在建模误差及宽温度范围下传统方法适应性差的问题,设计一种自适应增益滑模观测器(adaptive gain sliding mode observer,AGSMO)以提高宽温域SOC估计精度。采用二阶RC等效电路模型构造适用于AGSMO的状态方程,并结合遗忘因子最小二乘法(forgetting factor recursive least square,FFRLS)完成模型参数辨识。利用等效控制思想构建状态误差的等效表达式,基于此设计滑模观测器,同时采用自适应增益提高收敛速度并抑制抖振。结合案例应用仿真,结果表明:AGSMO在美国联邦城市运行工况FUDS和高加速循环工况US06的不同初值下均可实现SOC的准确估计,并通过上述两种工况验证宽温域环境下AGSMO相较于滑模观测器(sliding mode observer,SMO)、扩展卡尔曼滤波(extended Kalman filter,EKF)具有更好的估计精度及收敛速度,均方根误差不超过0.68%,且在温域两端呈现强鲁棒性。展开更多
Li-ion batteries are widely used in electric vehicles(EVs).However,the accuracy of online SOC estimation is still challenging due to the time-varying parameters in batteries.This paper proposes a decoupling multiple f...Li-ion batteries are widely used in electric vehicles(EVs).However,the accuracy of online SOC estimation is still challenging due to the time-varying parameters in batteries.This paper proposes a decoupling multiple forgetting factors recursive least squares method(DMFFRLS)for EV battery parameter identification.The errors caused by the different parameters are separated and each parameter is tracked independently taking into account the different physical characteristics of the battery parameters.The Thevenin equivalent circuit model(ECM)is employed considering the complexity of battery management system(BMS)on the basis of comparative analysis of several common battery ECMs.In addition,decoupling multiple forgetting factors are used to update the covariance due to different degrees of error of each parameter in the identification process.Numerous experiments are employed to verify the proposed DMFFRLS method.The parameters for commonly used LiFePO4(LFP),Li(NiCoMn)O2(NCM)battery cells and battery packs are identified based on the proposed DMFFRLS method and three conventional methods.The experimental results show that the error of the DMFFRLS method is less than 15 mV,which is significantly lower than the conventional methods.The proposed DMFFRLS shows good performance for parameter identification on different kind of batteries,and provides a basis for state of charge(SOC)estimation and BMS design of EVs.展开更多
The quarter model of an active suspension is established in the form of controllable autoregressive moving average （CARMA） model. An accelerometer can be mounted on the wheel hub for measuring road disturbance; this...The quarter model of an active suspension is established in the form of controllable autoregressive moving average （CARMA） model. An accelerometer can be mounted on the wheel hub for measuring road disturbance; this signal is used to identify the CARMA model parameters by recursive forgetting factors least square method. The linear quadratic integral （LQI） control method for the active suspension is presented. The LQI control algorithm is fit for vehicle suspension control, for the control performance index can comprise multi controlled variables. The simulation results show that the vertical acceleration and suspension travel both are decreased with the LQI control in the low frequency band, and the suspension travel is increased with the LQI control in the middle or high frequency band. The suspension travel is very small in the middle or high frequency band, the suspension bottoming stop will not happen, so the vehicle ride quality can be improved apparently by the LQI control.展开更多
An intuitive method for circle fitting is proposed. Assuming an approximate circle(CA,n) for the fitting of some scattered points, it can be imagined that every point would apply a force to CA,n, which all together fo...An intuitive method for circle fitting is proposed. Assuming an approximate circle(CA,n) for the fitting of some scattered points, it can be imagined that every point would apply a force to CA,n, which all together form an overall effect that "draws" CA,n towards best fitting to the group of points. The basic element of the force is called circular attracting factor(CAF) which is defined as a real scalar in a radial direction of CA,n. An iterative algorithm based on this idea is proposed, and the convergence and accuracy are analyzed. The algorithm converges uniformly which is proved by the analysis of Lyapunov function, and the accuracy of the algorithm is in accord with that of geometric least squares of circle fitting. The algorithm is adopted to circle detection in grayscale images, in which the transferring to binary images is not required, and thus the algorithm is less sensitive to lightening and background noise. The main point for the adaption is the calculation of CAF which is extended in radial directions of CA,n for the whole image. All pixels would apply forces to CA,n, and the overall effect of forces would be equivalent to a force from the centroid of pixels to CA,n. The forces from would-be edge pixels would overweigh that from noisy pixels, so the following approximate circle would be of better fitting. To reduce the amount of calculation, pixels are only used in an annular area including the boundary of CA,n just in between for the calculation of CAF. Examples are given, showing the process of circle fitting of scattered points around a circle from an initial assuming circle, comparing the fitting results for scattered points from some related literature, applying the method proposed for circular edge detection in grayscale images with noise, and/or with only partial arc of a circle, and for circle detection in BGA inspection.展开更多
In this paper we give a parallel algorithm for obtaining the eigenvalues and eigenvectors of a matrix.The practical background of this algorithm is the numerical computation in conjunction with the symbolic computation.
文摘A polynomial model, time origin shifting model(TOSM, is used to describe the trajectory of a moving target .Based on TOSM, a recursive laeast squares(RLS) algorithm with varied forgetting factor is derived for tracking of a non-maneuvering target. In order to apply this algorithm to maneuvering targets tracking ,a tracking signal is performed on-line to determine what kind of TOSm will be in effect to track a target with different dynamics. An effective multiple model least squares filtering and forecasting method dadpted to real tracking of a maneuvering target is formulated. The algorithm is computationally more effcient than Kalman filter and the percentage improvement from simulations show both of them are considerably alike to some extent.
基金Project supported by the National Natural Science Foundation of China (No. 60272079), and the Hi-Tech Research and Development Program (863) of China (No. 2003AA123310)
文摘Considering that channel estimation plays a crucial role in coherent detection, this paper addresses a method of Recursive-least-squares (RLS) channel estimation with adaptive forgetting factor in wireless space-time coded multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Because there are three different forgetting factor scenarios including adaptive, two-step and conventional ones applied to RLS channel estimation, this paper describes the principle of RLS channel estimation and analyzes the impact of different forgetting factor scenarios on the performances of RLS channel estimation. Simulation results proved that the RLS algorithm with adaptive forgetting factor (RLS-A) outperformed that with two-step forgetting factor (RLS-T) or with conventional forgetting factor (RLS-C) in both estimation accuracy and robustness over the multiple-input multiple-output (MIMO) channel, i.e., a wide-sense stationary uncorrelated scattering (WSSUS) and frequency-selective slowly fading channel. Hence, we can employ the RLS-A method by adjusting forgetting factor adaptively to track and estimate channel state parameters successfully in space-time coded MIMO-OFDM systems.
文摘针对多种电机采用的控制器模型也存在不同,电机参数存在多样性,并且针对多种工况下,电机在工作过程中存在参数变化、负载扰动等情况,导致电机参数辨识精度不高、电机-控制器模型失配等问题,提出了一种改进递归最小二乘法(recursive least squares,RLS)算法进行多种工况下多电机参数失配诊断。针对传统的递归最小二乘法在进行在线电机参数辨识时,容易固遗忘因子影响,存在跟随速度慢、抗干扰性差等问题,在原始递归最小二乘法基础上引入了随系统工况变化而变化的“变遗忘因子”,提高电机参数的跟踪速度和抗负载扰动能力;为验证改进后的递归最小二乘法是否具有可靠性、鲁棒性和泛化性,分别设置了5种假设工况,并进行多组实验对比,通过分析电机速度响应、d-q轴电流以及量化分析转矩跟踪和R_(s)参数辨识精度等,验证改进后的算法具有较强的鲁棒性和泛化性;并通过分析性能指标数据,主要包括平均速度、平均q轴电流等,得出改进后算法分析数据的有效性。
文摘荷电状态(state of charge,SOC)的准确估计对延长电池寿命、减少事故发生至关重要。针对锂电池系统存在建模误差及宽温度范围下传统方法适应性差的问题,设计一种自适应增益滑模观测器(adaptive gain sliding mode observer,AGSMO)以提高宽温域SOC估计精度。采用二阶RC等效电路模型构造适用于AGSMO的状态方程,并结合遗忘因子最小二乘法(forgetting factor recursive least square,FFRLS)完成模型参数辨识。利用等效控制思想构建状态误差的等效表达式,基于此设计滑模观测器,同时采用自适应增益提高收敛速度并抑制抖振。结合案例应用仿真,结果表明:AGSMO在美国联邦城市运行工况FUDS和高加速循环工况US06的不同初值下均可实现SOC的准确估计,并通过上述两种工况验证宽温域环境下AGSMO相较于滑模观测器(sliding mode observer,SMO)、扩展卡尔曼滤波(extended Kalman filter,EKF)具有更好的估计精度及收敛速度,均方根误差不超过0.68%,且在温域两端呈现强鲁棒性。
基金This work was supported by Science and Technology Project of State Grid Corporation of China(5202011600U5).
文摘Li-ion batteries are widely used in electric vehicles(EVs).However,the accuracy of online SOC estimation is still challenging due to the time-varying parameters in batteries.This paper proposes a decoupling multiple forgetting factors recursive least squares method(DMFFRLS)for EV battery parameter identification.The errors caused by the different parameters are separated and each parameter is tracked independently taking into account the different physical characteristics of the battery parameters.The Thevenin equivalent circuit model(ECM)is employed considering the complexity of battery management system(BMS)on the basis of comparative analysis of several common battery ECMs.In addition,decoupling multiple forgetting factors are used to update the covariance due to different degrees of error of each parameter in the identification process.Numerous experiments are employed to verify the proposed DMFFRLS method.The parameters for commonly used LiFePO4(LFP),Li(NiCoMn)O2(NCM)battery cells and battery packs are identified based on the proposed DMFFRLS method and three conventional methods.The experimental results show that the error of the DMFFRLS method is less than 15 mV,which is significantly lower than the conventional methods.The proposed DMFFRLS shows good performance for parameter identification on different kind of batteries,and provides a basis for state of charge(SOC)estimation and BMS design of EVs.
文摘The quarter model of an active suspension is established in the form of controllable autoregressive moving average （CARMA） model. An accelerometer can be mounted on the wheel hub for measuring road disturbance; this signal is used to identify the CARMA model parameters by recursive forgetting factors least square method. The linear quadratic integral （LQI） control method for the active suspension is presented. The LQI control algorithm is fit for vehicle suspension control, for the control performance index can comprise multi controlled variables. The simulation results show that the vertical acceleration and suspension travel both are decreased with the LQI control in the low frequency band, and the suspension travel is increased with the LQI control in the middle or high frequency band. The suspension travel is very small in the middle or high frequency band, the suspension bottoming stop will not happen, so the vehicle ride quality can be improved apparently by the LQI control.
基金Project(2013CB035504) supported by the National Basic Research Program of ChinaProject(2012zzts078) supported by the Fundamental Research Funds for the Central Universities of Central South University,ChinaProject(2009ZX02038) supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China
文摘An intuitive method for circle fitting is proposed. Assuming an approximate circle(CA,n) for the fitting of some scattered points, it can be imagined that every point would apply a force to CA,n, which all together form an overall effect that "draws" CA,n towards best fitting to the group of points. The basic element of the force is called circular attracting factor(CAF) which is defined as a real scalar in a radial direction of CA,n. An iterative algorithm based on this idea is proposed, and the convergence and accuracy are analyzed. The algorithm converges uniformly which is proved by the analysis of Lyapunov function, and the accuracy of the algorithm is in accord with that of geometric least squares of circle fitting. The algorithm is adopted to circle detection in grayscale images, in which the transferring to binary images is not required, and thus the algorithm is less sensitive to lightening and background noise. The main point for the adaption is the calculation of CAF which is extended in radial directions of CA,n for the whole image. All pixels would apply forces to CA,n, and the overall effect of forces would be equivalent to a force from the centroid of pixels to CA,n. The forces from would-be edge pixels would overweigh that from noisy pixels, so the following approximate circle would be of better fitting. To reduce the amount of calculation, pixels are only used in an annular area including the boundary of CA,n just in between for the calculation of CAF. Examples are given, showing the process of circle fitting of scattered points around a circle from an initial assuming circle, comparing the fitting results for scattered points from some related literature, applying the method proposed for circular edge detection in grayscale images with noise, and/or with only partial arc of a circle, and for circle detection in BGA inspection.
文摘In this paper we give a parallel algorithm for obtaining the eigenvalues and eigenvectors of a matrix.The practical background of this algorithm is the numerical computation in conjunction with the symbolic computation.
