This paper proposes a steady-state errors correction(SSEC)method for eliminating measurement errors.This method is based on the detections of error signal E(s)and output C(s)which generate an expected output R(s).In c...This paper proposes a steady-state errors correction(SSEC)method for eliminating measurement errors.This method is based on the detections of error signal E(s)and output C(s)which generate an expected output R(s).In comparison with the conventional solutions which are based on detecting the expected output R(s)and output C(s)to obtain error signal E(s),the measurement errors are eliminated even the error might be at a significant level.Moreover,it is possible that the individual debugging by regulating the coefficient K for every member of the multiple objectives achieves the optimization of the open loop gain.Therefore,this simple method can be applied to the weak coupling and multiple objectives system,which is usually controlled by complex controller.The principle of eliminating measurement errors is derived analytically,and the advantages comparing with the conventional solutions are depicted.Based on the SSEC method analysis,an application of this method for an active power filter(APF)is investigated and the effectiveness and viability of the scheme are demonstrated through the simulation and experimental verifications.展开更多
Based on the concept of the constitutive relation error along with the residuals of both the origin and the dual problems, a goal-oriented error estimation method with extended degrees of freedom is developed. It lead...Based on the concept of the constitutive relation error along with the residuals of both the origin and the dual problems, a goal-oriented error estimation method with extended degrees of freedom is developed. It leads to the high quality locM error bounds in the problem of the direct-solution steady-state dynamic analysis with a frequency-domain finite element, which involves the enrichments with plural variable basis functions. The solution of the steady-state dynamic procedure calculates the harmonic response directly in terms of the physical degrees of freedom in the model, which uses the mass, damping, and stiffness matrices of the system. A three-dimensional finite element example is carried out to illustrate the computational procedures.展开更多
在车辆高速剧烈运动场景下,现有激光雷达-惯性里程计(LiDAR-inertial odometry,LIO)因IMU前向传播误差的快速累积,导致车辆的运动畸变补偿精度下降,进而引发"补偿误差-配准误差-状态估计误差"的级联效应,最终造成车辆定位轨...在车辆高速剧烈运动场景下,现有激光雷达-惯性里程计(LiDAR-inertial odometry,LIO)因IMU前向传播误差的快速累积,导致车辆的运动畸变补偿精度下降,进而引发"补偿误差-配准误差-状态估计误差"的级联效应,最终造成车辆定位轨迹显著偏离真实状态,本文提出了基于迭代误差卡尔曼滤波(iterated error-state Kalman filter,IESKF)的自适应激光雷达-惯性里程计(state-adaptive update LiDAR-inertial odometry,SAU-LIO)。首先,提出基于协方差特征值阈值的动态调整策略,以实时监测LIO误差累积趋势,自适应缩短状态更新时间间隔,有效抑制剧烈运动下的误差发散;其次,结合线特征与面特征的联合提取策略,构建概率观测模型,通过观测协方差矩阵约束实现不同置信度特征的最优加权融合,实现环境特征的有效利用。最后,基于NCLT(the university of Michigan north campus long-term vision and LIDAR dataset)、UTBM(EU long-term dataset with multiple sensors for autonomous driving)标准数据集及实车试验平台的验证结果表明:SAU-LIO算法在保证实时性的前提下,与对比算法相比具有更高的定位精度,在低速工况下,平均定位误差较次优的对比算法减小14.3%,在组合工况下,平均定位误差较次优的对比算法减小9.4%。展开更多
Multistation machining process is widely applied in contemporary manufacturing environment. Modeling of variation propagation in multistation machining process is one of the most important research scenarios. Due to t...Multistation machining process is widely applied in contemporary manufacturing environment. Modeling of variation propagation in multistation machining process is one of the most important research scenarios. Due to the existence of multiple variation streams, it is challenging to model and analyze variation propagation in a multi-station system. Current approaches to error modeling for multistation machining process are not explicit enough for error control and ensuring final product quality. In this paper, a mathematic model to depict the part dimensional variation of the complex multistation manufacturing process is formulated. A linear state space dimensional error propagation equation is established through kinematics analysis of the influence of locating parameter variations and locating datum variations on dimensional errors, so the dimensional error accumulation and transformation within the multistation process are quantitatively described. A systematic procedure to build the model is presented, which enhances the way to determine the variation sources in complex machining systems. A simple two-dimensional example is used to illustrate the proposed procedures. Finally, an industrial case of multistation machining part in a manufacturing shop is given to testify the validation and practicability of the method. The proposed analytical model is essential to quality control and improvement for multistation systems in machining quality forecasting and design optimization.展开更多
In this paper, an analogue correction method of errors （ACE） based on a complicated atmospheric model is further developed and applied to numerical weather prediction （NWP）. The analysis shows that the ACE can eff...In this paper, an analogue correction method of errors （ACE） based on a complicated atmospheric model is further developed and applied to numerical weather prediction （NWP）. The analysis shows that the ACE can effectively reduce model errors by combining the statistical analogue method with the dynamical model together in order that the information of plenty of historical data is utilized in the current complicated NWP model, Furthermore, in the ACE, the differences of the similarities between different historical analogues and the current initial state are considered as the weights for estimating model errors. The results of daily, decad and monthly prediction experiments on a complicated T63 atmospheric model show that the performance of the ACE by correcting model errors based on the estimation of the errors of 4 historical analogue predictions is not only better than that of the scheme of only introducing the correction of the errors of every single analogue prediction, but is also better than that of the T63 model.展开更多
This paper investigates the effect of the Phase Angle Error of a Constant Amplitude Voltage signal in determining the Total Vector Error (TVE) of the Phasor Measurement Unit (PMU) using MATLAB/Simulink. The phase angl...This paper investigates the effect of the Phase Angle Error of a Constant Amplitude Voltage signal in determining the Total Vector Error (TVE) of the Phasor Measurement Unit (PMU) using MATLAB/Simulink. The phase angle error is measured as a function of time in microseconds at four points on the IEEE 14-bus system. When the 1 pps Global Positioning System (GPS) signal to the PMU is lost, sampling of voltage signals on the power grid is done at different rates as it is a function of time. The relationship between the PMU measured signal phase angle and the sampling rate is established by injecting a constant amplitude signal at two different points on the grid. In the simulation, 64 cycles per second is used as the reference while 24 cycles per second is used to represent the fault condition. Results show that a change in the sampling rate from 64 bps to 24 bps in the PMUs resulted in phase angle error in the voltage signals measured by the PMU at four VI Measurement points. The phase angle error measurement that was determined as a time function was used to determine the TVE. Results show that (TVE) was more than 1% in all the cases.展开更多
This paper presents the harmonic state estimation (HSE) based on the Total Least Squares (TLS) through comprehensively considering the harmonic network parameter error and measurement system error. The proposed approa...This paper presents the harmonic state estimation (HSE) based on the Total Least Squares (TLS) through comprehensively considering the harmonic network parameter error and measurement system error. The proposed approach is tested on the IEEE 14–bus harmonic testing system. The satisfied results are obtained.展开更多
基金National Natural Science Foundation of China(No.61273172)
文摘This paper proposes a steady-state errors correction(SSEC)method for eliminating measurement errors.This method is based on the detections of error signal E(s)and output C(s)which generate an expected output R(s).In comparison with the conventional solutions which are based on detecting the expected output R(s)and output C(s)to obtain error signal E(s),the measurement errors are eliminated even the error might be at a significant level.Moreover,it is possible that the individual debugging by regulating the coefficient K for every member of the multiple objectives achieves the optimization of the open loop gain.Therefore,this simple method can be applied to the weak coupling and multiple objectives system,which is usually controlled by complex controller.The principle of eliminating measurement errors is derived analytically,and the advantages comparing with the conventional solutions are depicted.Based on the SSEC method analysis,an application of this method for an active power filter(APF)is investigated and the effectiveness and viability of the scheme are demonstrated through the simulation and experimental verifications.
基金Project supported by the National Natural Science Foundation of China (No. 10876100)
文摘Based on the concept of the constitutive relation error along with the residuals of both the origin and the dual problems, a goal-oriented error estimation method with extended degrees of freedom is developed. It leads to the high quality locM error bounds in the problem of the direct-solution steady-state dynamic analysis with a frequency-domain finite element, which involves the enrichments with plural variable basis functions. The solution of the steady-state dynamic procedure calculates the harmonic response directly in terms of the physical degrees of freedom in the model, which uses the mass, damping, and stiffness matrices of the system. A three-dimensional finite element example is carried out to illustrate the computational procedures.
文摘在车辆高速剧烈运动场景下,现有激光雷达-惯性里程计(LiDAR-inertial odometry,LIO)因IMU前向传播误差的快速累积,导致车辆的运动畸变补偿精度下降,进而引发"补偿误差-配准误差-状态估计误差"的级联效应,最终造成车辆定位轨迹显著偏离真实状态,本文提出了基于迭代误差卡尔曼滤波(iterated error-state Kalman filter,IESKF)的自适应激光雷达-惯性里程计(state-adaptive update LiDAR-inertial odometry,SAU-LIO)。首先,提出基于协方差特征值阈值的动态调整策略,以实时监测LIO误差累积趋势,自适应缩短状态更新时间间隔,有效抑制剧烈运动下的误差发散;其次,结合线特征与面特征的联合提取策略,构建概率观测模型,通过观测协方差矩阵约束实现不同置信度特征的最优加权融合,实现环境特征的有效利用。最后,基于NCLT(the university of Michigan north campus long-term vision and LIDAR dataset)、UTBM(EU long-term dataset with multiple sensors for autonomous driving)标准数据集及实车试验平台的验证结果表明:SAU-LIO算法在保证实时性的前提下,与对比算法相比具有更高的定位精度,在低速工况下,平均定位误差较次优的对比算法减小14.3%,在组合工况下,平均定位误差较次优的对比算法减小9.4%。
基金supported by National Department Fundamental Research Foundation of China (Grant No. B222090014)National Department Technology Fundatmental Foundaiton of China (Grant No. C172009C001)
文摘Multistation machining process is widely applied in contemporary manufacturing environment. Modeling of variation propagation in multistation machining process is one of the most important research scenarios. Due to the existence of multiple variation streams, it is challenging to model and analyze variation propagation in a multi-station system. Current approaches to error modeling for multistation machining process are not explicit enough for error control and ensuring final product quality. In this paper, a mathematic model to depict the part dimensional variation of the complex multistation manufacturing process is formulated. A linear state space dimensional error propagation equation is established through kinematics analysis of the influence of locating parameter variations and locating datum variations on dimensional errors, so the dimensional error accumulation and transformation within the multistation process are quantitatively described. A systematic procedure to build the model is presented, which enhances the way to determine the variation sources in complex machining systems. A simple two-dimensional example is used to illustrate the proposed procedures. Finally, an industrial case of multistation machining part in a manufacturing shop is given to testify the validation and practicability of the method. The proposed analytical model is essential to quality control and improvement for multistation systems in machining quality forecasting and design optimization.
基金Project supported by the National Natural Science Foundation of China （Grant Nos 40575036 and 40325015）.Acknowledgement The authors thank Drs Zhang Pei-Qun and Bao Ming very much for their valuable comments on the present paper.
文摘In this paper, an analogue correction method of errors （ACE） based on a complicated atmospheric model is further developed and applied to numerical weather prediction （NWP）. The analysis shows that the ACE can effectively reduce model errors by combining the statistical analogue method with the dynamical model together in order that the information of plenty of historical data is utilized in the current complicated NWP model, Furthermore, in the ACE, the differences of the similarities between different historical analogues and the current initial state are considered as the weights for estimating model errors. The results of daily, decad and monthly prediction experiments on a complicated T63 atmospheric model show that the performance of the ACE by correcting model errors based on the estimation of the errors of 4 historical analogue predictions is not only better than that of the scheme of only introducing the correction of the errors of every single analogue prediction, but is also better than that of the T63 model.
文摘This paper investigates the effect of the Phase Angle Error of a Constant Amplitude Voltage signal in determining the Total Vector Error (TVE) of the Phasor Measurement Unit (PMU) using MATLAB/Simulink. The phase angle error is measured as a function of time in microseconds at four points on the IEEE 14-bus system. When the 1 pps Global Positioning System (GPS) signal to the PMU is lost, sampling of voltage signals on the power grid is done at different rates as it is a function of time. The relationship between the PMU measured signal phase angle and the sampling rate is established by injecting a constant amplitude signal at two different points on the grid. In the simulation, 64 cycles per second is used as the reference while 24 cycles per second is used to represent the fault condition. Results show that a change in the sampling rate from 64 bps to 24 bps in the PMUs resulted in phase angle error in the voltage signals measured by the PMU at four VI Measurement points. The phase angle error measurement that was determined as a time function was used to determine the TVE. Results show that (TVE) was more than 1% in all the cases.
文摘This paper presents the harmonic state estimation (HSE) based on the Total Least Squares (TLS) through comprehensively considering the harmonic network parameter error and measurement system error. The proposed approach is tested on the IEEE 14–bus harmonic testing system. The satisfied results are obtained.
