Power System State Estimation Solution With Zero Injection Constraints Using Modified Newton Method and Fast Decoupled Method in Polar Coordinate

如何保证零注入节点的注入功率在状态估计结果中严格为0是电力系统状态估计研究中的重要问题。在直角坐标下,由于零注入约束为线性约束,可使用修正牛顿法来有效地解决这一问题。因此,借鉴直角坐标下修正牛顿法的思路,提出了极坐标下的修正牛顿法和修正快速解耦估计。这些方法的计算流程与传统的极坐标下的牛顿法和快速解耦估计非常相似,计算速度与大权重法相当,同时能够保证零注入约束严格满足。仿真结果验证了所得结论。

Aircraft attitude estimation of MEMS sensor based on modified particle filter

The non-linearity problem of aircraft system could not be overcome by using the MEMS sensor only.In order to improve the accuracy of aerial vehicle attitude,an aircraft attitude estimation of the MEMS sensor based on modified particle filter is proposed.The aircraft attitude is optimized by the conjugate gradient method,and the drift error of gyroscope is reduced.Moreover,the particle weight is updated by the observed value to obtain an optimized state estimate.Finally,the conjugate gradient method and the modified particle filter are weightily combined to determine the optimal weighting factor.The attitude estimation is carried out with STM32 and MEMS sensor as the core to design system.The experimental results show that the static and dynamic attitude estimation performances of the aircraft are improved.The performances are well,the attitude data is relatively stable,and the tracking characteristics are better.Moreover,it has better robustness and stability.

Modified OMP method for multi-target parameter estimation in frequency-agile distributed MIMO radar

Introducing frequency agility into a distributed multipleinput multiple-output(MIMO)radar can significantly enhance its anti-jamming ability.However,it would cause the sidelobe pedestal problem in multi-target parameter estimation.Sparse recovery is an effective way to address this problem,but it cannot be directly utilized for multi-target parameter estimation in frequency-agile distributed MIMO radars due to spatial diversity.In this paper,we propose an algorithm for multi-target parameter estimation according to the signal model of frequency-agile distributed MIMO radars,by modifying the orthogonal matching pursuit(OMP)algorithm.The effectiveness of the proposed method is then verified by simulation results.

Systematic error real-time registration based onmodified input estimation

In order to estimate the systematic error in the processof maneuvering target adaptive tracking, a new method is proposed.The proposed method is a linear tracking scheme basedon a modified input estimation approach. A special augmentationin the state space model is considered, in which both the systematicerror and the unknown input vector are attached to thestate vector. Then, an augmented state model and a measurementmodel are established in the case of systematic error, andthe corresponding filter formulas are also given. In the proposedscheme, the original state, the acceleration and the systematicerror vector can be estimated simultaneously. This method can notonly solve the maneuvering target adaptive tracking problem in thecase of systematic error, but also give the system error value inreal time. Simulation results show that the proposed tracking algorithmoperates in both the non-maneuvering and the maneuveringmodes, and the original state, the acceleration and the systematicerror vector can be estimated simultaneously.

Flight Vehicle Attitude Determination Using the Modified Rodrigues Parameters

There are two attitude estimation algorithms based on the different representations of attitude errors when modified Rodrigues parameters are applied to attitude estimation. The first is multiplicative error attitude estimator （MEAE）, whose attitude error is expressed by the modified Rodrigues parameters representing the rotation from the estimated to the true attitude. The second is subtractive error attitude estimator （SEAE）, whose attitude error is expressed by the arithmetic difference between the true and the estimated attitudes. It is proved that the two algorithms are equivalent in the case of small attitude errors. It is possible to describe rotation without encountering singularity by switching between the modified Rodrigues parameters and their shadow parameters. The attitude parameter switching does not bring disturbance to MEAE, but it does to SEAE. This article introduces a modification to eliminate the disturbance on SEAE, and simulation results demonstrate the efficacy of the presented algorithm.

Modified unscented particle filter for nonlinear Bayesian tracking

A modified unscented particle filtering scheme for nonlinear tracking is proposed, in view of the potential drawbacks （such as, particle impoverishment and numerical sensitivity in calculating the prior） of the conventional unscented particle filter （UPF） confronted in practice. Specifically, a different derivation of the importance weight is presented in detail. The proposed method can avoid the calculation of the prior and reduce the effects of the impoverishment problem caused by sampling from the proposal distribution, Simulations have been performed using two illustrative examples and results have been provided to demonstrate the validity of the modified UPF as well as its improved performance over the conventional one.

A modified Tikhonov regularization method for a Cauchy problem of a time fractional diffusion equation

In this paper,we consider a Cauchy problem of the time fractional diffusion equation(TFDE)in x∈[0,L].This problem is ubiquitous in science and engineering applications.The illposedness of the Cauchy problem is explained by its solution in frequency domain.Furthermore,the problem is formulated into a minimization problem with a modified Tikhonov regularization method.The gradient of the regularization functional based on an adjoint problem is deduced and the standard conjugate gradient method is presented for solving the minimization problem.The error estimates for the regularized solutions are obtained under Hp norm priori bound assumptions.Finally,numerical examples illustrate the effectiveness of the proposed method.

ON AMODIFIED NEWTON'S METHOD AND CONVERGENCE

In this paper we discuss the convergence of a modified Newton’s method presented by A. Ostrowski [1] and J.F. Traub [2], which has quadratic convergence order but reduces one evaluation of the derivative at every two steps compared with Newton’s method. A convergence theorem is established by using a weak condition a≤3-2(21/2) and a sharp error estimate is given about the iterative sequence.

The Initial Boundary Value Problem for Modified Zakharov System

In this paper, we consider the initial boudary value problem for modified Zakharov system in 3 dimensions with small initial condition. By using the continuity lemma and the linear interpolation theory, together with the properties of Sobolev spaces and the Galerkin method, we obtain the existence and uniqueness of the global solution.

二元逻辑回归模型中的修正Liu估计

在二元逻辑回归模型中,基于修正岭型估计和Liu估计的思想,提出了一类新的有偏估计作为极大似然估计的替代估计,以期克服多重共线性的影响。在均方误差矩阵意义下,探讨得到了修正Liu估计优于Liu估计、修正岭型估计、极大似然估计等的条件,通过数值模拟和实证分析对部分理论结果在均方误差准则下进行了验证。结果表明,在一定条件下,当模型存在多重共线性时,修正Liu估计优于Liu估计、修正岭型估计以及极大似然估计。

基于Born-Jordan分布的LFM-BPSK信号的参数估计

对线性调频-二进制相位编码(LFM-BPSK)复合调制信号的参数估计,现有方法在低信噪比(SNR)环境下估计精度较低。针对该问题,文中推导出了LFM-BPSK信号的Born-Jordan(BJD)时频分布,分析了LFM-BPSK信号的时频特性,并提出了基于BJD时频分布的参数估计算法。首先,该算法在BJD时频变换的基础上使用霍夫变换对LFM-BPSK信号初始频率和调频斜率进行估计,并将二维的BJD时频变换转化为一维时域信号,通过降维后的时域信号求解码元宽度;然后,为了探寻参数估计的理论下界,文中还推导了LFM-BPSK信号参数估计的修正克拉美罗下界(MCRLB);最后,利用蒙特卡洛实验对三个参数进行了测试。仿真实验表明,文中算法在低SNR下的参数估计精度明显优于现有的算法,其性能接近MCRLB。

Research on Adaptive Cluster Sampling Method Based on PPS

This paper introduces the principle of PPS-based adaptive cluster sampling method and its modified HH estimator and HT estimator calculation method. It compares PPS-based adaptive cluster sampling method with SRS sampling and SRS-based adaptive group. The difference between the group sampling and the advantages and scope of the PPS adaptive cluster sampling method are analyzed. According to the case analysis, the relevant conclusions are drawn: 1) The adaptive cluster sampling method is more accurate than the SRS sampling;2) SRS adaptive The HT estimator of the cluster sampling is more stable than the HH estimator;3) The two estimators of the PPS adaptive cluster sampling method have little difference in the estimation of the population mean, but the HT estimator variance is smaller and more suitable;4) PPS The HH estimator of adaptive cluster sampling is the same as the HH estimator of SRS adaptive cluster sampling, but the variance is larger and unstable.

基于改进无迹卡尔曼滤波器算法的滞回模型参数识别研究

地震产生的周期荷载作用下,钢混桥墩结构表现出滞回行为。为描述滞回行为,研究者提出各类滞回模型,其中BWBN(Bouc-Wen-Baber-Noori)模型可以描述结构滞回行为的强度退化、刚度退化和捏拢效应等典型特征。此外,无迹卡尔曼滤波器UKF(unscented Kalman filter)算法是识别BWBN模型参数的高效方法,但当参数初始值与真实值的偏差过大及缺乏对系统的整体估计时,UKF算法识别过程受到局限。本文改进生成样本点规则,提出改进UKF算法。数值模拟结果表明,在无噪声条件下,改进UKF算法识别得到的参数估计值与准确值的误差平均为1.51%,最大误差为4%;在2%均方根RMS(root mean square)高斯白噪声条件下,误差平均为5.43%,最大误差为18%;在5%RMS高斯白噪声条件下,误差平均为8.9%,最大误差为26%和22%。改进UKF算法识别非线性滞回系统状态估计和BWBN模型参数更加准确和稳定。

The A Priori and A Posteriori Error Estimates for Modified Interior Transmission Eigenvalue Problem in Inverse Scattering

In this paper,we discuss the conforming finite element method for a modified interior transmission eigenvalues problem.We present a complete theoretical analysis for the method,including the a priori and a posteriori error estimates.The theoretical analysis is conducted under the assumption of low regularity on the solution.We prove the reliability and efficiency of the a posteriori error estimators for eigenfunctions up to higher order terms,and we also analyze the reliability of estimators for eigenvalues.Finally,we report numerical experiments to show that our posteriori error estimator is effective and the approximations can reach the optimal convergence order.The numerical results also indicate that the conforming finite element eigenvalues approximate the exact ones from below,and there exists a monotonic relationship between the conforming finite element eigenvalues and the refractive index through numerical experiments.

二元逻辑回归模型中的一阶近似刀切修正岭型估计

在二元逻辑回归模型中,基于一阶近似修正岭型估计方法和刀切法提出了一类新估计,即一阶近似刀切修正岭型估计,探讨得到了新估计在均方误差等准则下优于一阶近似修正岭型估计、一阶近似极大似然估计的充分条件,同时通过数值模拟和实证分析对部分理论结果进行了说明,结果显示,当满足理论结果中的条件时,一阶近似刀切修正岭型估计在相关准则下优于一阶近似修正岭型估计、一阶近似极大似然估计。

六极外转子径向混合磁轴承转子位移自检测

为了解决六极混合磁轴承位移传感器体积大、成本高的问题,提出了一种改进粒子群优化算法最小二乘支持向量机的位移估计方法.首先,介绍六极外转子径向混合磁轴承的结构和工作原理,并推导其径向悬浮力的数学模型.其次,将改进的粒子群算法的惯性权重改变,以实现更快的迭代,并建立了基于最小二乘支持向量机的预测模型,根据改进的粒子群算法优化的参数对预测模型进行了仿真和验证,并比较了改进的粒子群算法和粒子群算法的预测值.最后,进行了静态悬浮实验、动态悬浮实验、扰动实验,验证了该位移估计方法的鲁棒性和稳定性.

基于盲超分辨的超大规模MIMO-OFDM信道与感知参数联合估计

面向未来6G网络,ISAC与XL-MIMO技术有机结合、共同演进,有望进一步提升ISAC性能。然而,XL-MIMO-ISAC中部署大量天线会产生近场效应,为准确获取CSI和目标参数信息带来关键挑战。为此,采用线性修改的原子范数最小化方法,建模毫米波通信信道和感知阵列响应这两种盲源之间极坐标域的子空间一致关联,并提出了一种基于盲超分辨技术的CSI与感知参数并行估计方案,以避免从叠加信号中串行估计通信信道与目标参数信息造成误差传播。将联合盲源估计建模为非完全观测条件下的低秩矩阵重构问题,并引入PSWF将问题转化为SDP。仿真结果验证了提出的算法在CSI精度和目标参数分辨率方面的有效性。

基于改进深度学习的光伏电站发电量精准估计

为实现对电站发电量的精准估计与测算,引入改进深度学习算法,以某光伏发电站为例,进行发电量精准估计方法的设计研究。计算光伏电站太阳辐照量,收集光伏电站功率、电流、电压等发电数据以及太阳辐射强度、温度、湿度等相关气象数据,并对收集到的光伏电站发电信息进行预处理;为排除光伏组件损失对发电量估算的影响,先进行光伏组件损失分析,再以此为依据对光伏电站发电量进行估计。实例应用结果表明该设计方法在应用中可以有效控制光伏电站发电量估计误差,提高发电量估计值的准确性与可靠性。

线性模型参数一类新的s-K估计

基于线性回归模型参数向量的先验信息提出一类新的s-K估计——改进s-K估计,并在均方误差阵意义下,得到了这类估计分别优于最小二乘估计、广义岭估计、Stein估计及s-K估计的充要条件.