Maximum Correntropy Kalman Filtering for Non-Gaussian Systems With State Saturations and Stochastic Nonlinearities

This paper tackles the maximum correntropy Kalman filtering problem for discrete time-varying non-Gaussian systems subject to state saturations and stochastic nonlinearities. The stochastic nonlinearities, which take the form of statemultiplicative noises, are introduced in systems to describe the phenomenon of nonlinear disturbances. To resist non-Gaussian noises, we consider a new performance index called maximum correntropy criterion(MCC) which describes the similarity between two stochastic variables. To enhance the “robustness” of the kernel parameter selection on the resultant filtering performance, the Cauchy kernel function is adopted to calculate the corresponding correntropy. The goal of this paper is to design a Kalman-type filter for the underlying systems via maximizing the correntropy between the system state and its estimate. By taking advantage of an upper bound on the one-step prediction error covariance, a modified MCC-based performance index is constructed. Subsequently, with the assistance of a fixed-point theorem, the filter gain is obtained by maximizing the proposed cost function. In addition, a sufficient condition is deduced to ensure the uniqueness of the fixed point. Finally, the validity of the filtering method is tested by simulating a numerical example.

Quantum Generalized Measurement and Deterministic Generation of Maximum Entangled Pure State

We propose the concept of the quantum generalized projector measurement （QGPM） for finite-dimensional quantum systems by studying the quantum generalized measurement. This research reveals a distinguished property of this quantum generalized measurement： no matter what the system state is prior to the measurement and what the result of the measurement occurs, the state of the system after the measurement can be collapsed into any specified pure state, i.e., the state of quantum system can be deterministically reduced to any specified pure state just by a single QGPM. Subsequently. QGPM can be used to deterministically generate the maximum entangled pure state for quantum systems. We give three concrete theoretic schemes of generating the maximum quantum entangled pure states for two 2-Jevel particles, three 2-level particles and two 3-Jevel particles, respectively.

Improving Accuracy of Estimating Two-Qubit States with Hedged Maximum Likelihood

As a widely used reconstruction algorithm in quantum state tomography, maximum likelihood estimation tends to assign a rank-deficient matrix, which decreases estimation accuracy for certain quantum states. Fortunately, hedged maximum likelihood estimation （HMLE） [Phys. Rev. Lett. 105 （2010）200504] was proposed to avoid this problem. Here we study more details about this proposal in the two-qubit case and further improve its performance. We ameliorate the HMLE method by updating the hedging function based on the purity of the estimated state. Both performances of HMLE and ameliorated HMLE are demonstrated by numerical simulation and experimental implementation on the Werner states of polarization-entangled photons.

Non Linear Dynamic Crack Model Applied to State Observers Methodology for Fault Detection, Localization and Evaluation in a Cantilever Beam

The purpose of this work is the study of a mathematical model to discretize cracks at continuous mechanical systems, applying all the available properties at computational algorithm using the methodology of state observers to detect, localize and evaluate the crack conditions, seeking the model limitations through an experiment developed at the mechanical department of UNESP, llha Solteira, S^o Paulo-Brazil. Three different notch sizes were placed, one by one, at the top surface of a cantilever beam （to be considered as a crack at the mechanical system） and harmonic forces were applied at the tip of the beam with three different frequencies, for each notch size, to obtain experimental data to run the diagnosis algorithm. From the results it was possible to infer that the observation system performance increases with the raising of the crack size, which can be explained by the model, that gets more accurate with bigger crack sizes, however, when the propagation of the crack is considered at the model, the diagnosis of the crack presence tends to be more difficult. It was also possible to conclude that the developed algorithm works properly for systems which excitation frequencies are higher than 20 Hz and different from the natural frequencies of the system, due to influence of dynamic response of the crack at the model.

Tool Wear State Recognition with Deep Transfer Learning Based on Spindle Vibration for Milling Process

The wear of metal cutting tools will progressively rise as the cutting time goes on. Wearing heavily on the toolwill generate significant noise and vibration, negatively impacting the accuracy of the forming and the surfaceintegrity of the workpiece. Hence, during the cutting process, it is imperative to continually monitor the tool wearstate andpromptly replace anyheavilyworn tools toguarantee thequality of the cutting.The conventional tool wearmonitoring models, which are based on machine learning, are specifically built for the intended cutting conditions.However, these models require retraining when the cutting conditions undergo any changes. This method has noapplication value if the cutting conditions frequently change. This manuscript proposes a method for monitoringtool wear basedonunsuperviseddeep transfer learning. Due to the similarity of the tool wear process under varyingworking conditions, a tool wear recognitionmodel that can adapt to both current and previous working conditionshas been developed by utilizing cutting monitoring data from history. To extract and classify cutting vibrationsignals, the unsupervised deep transfer learning network comprises a one-dimensional (1D) convolutional neuralnetwork (CNN) with a multi-layer perceptron (MLP). To achieve distribution alignment of deep features throughthe maximum mean discrepancy algorithm, a domain adaptive layer is embedded in the penultimate layer of thenetwork. A platformformonitoring tool wear during endmilling has been constructed. The proposedmethod wasverified through the execution of a full life test of end milling under multiple working conditions with a Cr12MoVsteel workpiece. Our experiments demonstrate that the transfer learning model maintains a classification accuracyof over 80%. In comparisonwith the most advanced tool wearmonitoring methods, the presentedmodel guaranteessuperior performance in the target domains.

Analysis of Maximum PowerPoint Tracking (MPPT) Adaptability in Inverters of the Three-Phase Photovoltaic Systems Integrated into the Electrical Grid of Congo-Brazzaville

This paper investigates the adaptability of Maximum Power Point Tracking (MPPT) algorithms in single-stage three-phase photovoltaic (PV) systems connected to the grid of Congo-Brazzaville and compares the attributes of various conventional, significance and novelty of controller system of the proposed of method and improved Incremental Conductance algorithms, Perturbation and Observation Techniques, and other Maximum Power Point Tracking (MPPT) algorithms in normal and partial shading conditions. Performance evaluation techniques are discussed on the basis of the dynamic parameters of the PV system although the control of this structure is relatively advanced technology but the conversion efficiency is difficult to improve due to increase in transformation series. The single stage topology has a simple topology with high reliability and efficiency because of high power consumption, but control algorithm is more complex because of its power convert main circuit a new strategy is being developed. This paper describes a method for maximum power point tracking (MPPT) in the single-stage and three single-phase PV grid-connected system. In the paper, the nonlinear output characteristics of the PV including I-V & P-V are obtained in changed solar insulations or temperature based on MATLAB, and the MPPT algorithm which is based on the P & O algorithm method, compared with Incremental Conductance, is also described, a dimensioning of the impedance adapter for better stabilization. A comparison SPWM and SVPWM control methods in the case of a grid connection applied to the electrical grid of Republic of Congo and their influences on the dynamic performance of the system and their impact in reducing the harmonic rate for better injection into the grid. The simulation model of three single-phase PV grid-connected system is built, and simulation results show the MPPT algorithm has excellent dynamic and static performances, which verifies the Incremental Conductance is effective for MPPT in the single-stage and three single-phase PV grid-connected system.

A circular zone counting method of identifying a Duffing oscillator state transition and determining the critical value in weak signal detection

Identifying state transition and determining the critical value of the Duffing oscillator are crucial to indicating external signal existence and have a great influence on detection accuracy in weak signal detection. A circular zone counting （CZC） method is proposed in this paper, by combining the Duffing oscillator＇s phase trajectory feature and numerical calculation for quickly and accurately identifying state transition and determining the critical value, to realize a high- efficiency weak signal detection. Detailed model analysis and method construction of the CZC method are introduced. Numerical experiments into the reliability of the proposed CZC method compared with the maximum Lyapunov exponent （MLE） method are carried out. The CZC method is demonstrated to have better detecting ability than the MLE method, and furthermore it is simpler and clearer in calculation to extend to engineering application.

NECESSARY CONDITIONS FOR OPTIMAL CONTROLS OF SEMILINEAR ELLIPTIC VARIATIONAL INEQUALITIES INVOLVING STATE CONSTRAINT

This paper deals with maximum principle for some optimal control problem governed by some elliptic variational inequalities. Some state constraints are discussed. The basic techniques used here are based on those in [1] and a new penalty functional defined in this paper.

Maximum confidence measurements via probabilistic quantum cloning

Probabilistic quantum cloning（PQC） cannot copy a set of linearly dependent quantum states.In this paper,we show that if incorrect copies are allowed to be produced,linearly dependent quantum states may also be cloned by the PQC.By exploiting this kind of PQC to clone a special set of three linearly dependent quantum states,we derive the upper bound of the maximum confidence measure of a set.An explicit transformation of the maximum confidence measure is presented.

THE OPTIMAL CONTROL OF DELAY CONTROL SYSTEMS WITH RESTRICTED STATE RIGHT ENDPOINT

In this paper, for the delay control system: (x) over dot (t)=f[x(t), x(t-1), u(t), t] t is an element of[t(0), t(1)] x(t)=psi(t) t is an element of[t(0), t(1)] with state right endpoint restricted by condition psi(k)[x(t(1))]=0 (k=1,2,..., l) a maximum principle is given. And as a specific example, this paper gives a maximum principle under the condition that partial stares right endpoints be completely fixed. Finally, this paper gives an example to explain the application of the main result of this paper. All the results are suitable for the control systems with multidelay as well.

ANALYTICAL SOLUTION FOR AXISYMMETRIC PROBLEM OF THICK LAMINATED CLOSED CANTILEVER SHELIS IN HAMILTON SYSTEM

By giving up any assumptions about displacement models and stress distribution,the mixed state Hamilton equation for the axisymmetric problem of the thick laminated closed cantilever cylindrical shells is established.An identical analytical solution is obtained for the thin,moderately thick and thick laminated closed cantilever cylindrical shells.All equations of elasticity can be satis- fied,and all elastic constants can be taken into account.

Pontryagin’s Maximum Principle for a Advection-Diffusion-Reaction Equation

In this paper we investigate optimal control problems governed by a advection-diffusion-reaction equation. We present a method for deriving conditions in the form of Pontryagin’s principle. The main tools used are the Ekeland’s variational principle combined with penalization and spike variation techniques.

Bending Stresses of Steel Web Tapered Tee Section Cantilevers

Although commonly used, no design method is available for steel web tapered tee section cantilevers. This paper investigates the bending stresses of such beams. Relationships between the maximum compressive stress and the degree of taper were investigated. An analytical model is presented to determine the location of the maximum stress when subjected to a uniformly distributed load or a point load at the free end and was validated using finite element analysis and physical tests. It was found that the maximum stress always occurs at the support when subjected to a uniformly distributed load. When subjected to a point load at the free end and the degree of taper is up to seven, it was found that Miller＇s equation could be used to determine the location of the maximum stress. However, it is shown that when the degree of taper is greater than seven, Miller＇s equation does not accurately predict the location and the analytical model should be used. It was also found that the location of the maximum stress was solely dependent on the degree of taper, while a geometric ratio, fl was required to determine the magnitude of the maximum stress. A simple method that predicts the magnitude of the maximum stress is proposed. The average error in the prediction of the magnitude of the maximum stress is found to be less than 1.0%.

基于固态断路器主动注入式直流故障测距方法

随着直流配电网的快速发展与深化应用,准确可靠的故障测距技术对直流故障检修和恢复至关重要。该文提出一种基于固态断路器(SSCB)主动注入式直流故障测距方法。首先,利用SSCB开断主动注入不同脉冲宽度的信号,并检测注入脉冲首末端和反射波首末端的时间差作为注入波形传播时间间隔,能够减小采样频率带来的误差。然后,提取电缆线路电压线模量作为检测量,削弱正负极线路之间的耦合作用,获得稳定波速。最后,基于小波变换原理提出改进自适应模极大值方法来检测脉冲首末端时刻,减小噪声和过渡电阻对测距精度的影响。仿真结果表明,基于SSCB主动注入式测距方法在直流配电网单极接地和极间短路故障情况下均能够实现准确且快速的定位。

大跨径斜拉桥施工阶段临时抗风措施对比分析

研究目的:大跨径斜拉桥在最大双悬臂施工状态下结构刚度较小,对风荷载引起的结构风致振动响应较为敏感。本文以受沿海台风影响区域的一座主跨316 m斜拉桥为研究对象,根据风洞试验确定主梁的气动三分力系数,对比分析不同风缆布置方案与不同临时墩布置方式对大桥风致响应控制效果的影响。研究结论:(1)增设临时风缆可使主梁竖弯基频提高22.0%~32.5%,对结构自身的扭转基频影响效果不显著;临时风缆对主梁竖向位移和主塔顺桥向位移控制有一定作用,固定位置在主梁最大悬臂长度的80%~90%范围内效果较好;(2)临时墩的抗风减振效果显著优于临时风缆,临时墩的设置使主梁悬臂端竖向位移响应降低了53.5%~65.5%,对主梁悬臂根部的顺桥向弯矩与横桥向弯矩的控制效果较为明显,降幅11.7%~58.8%;(3)在选择桥梁临时抗风措施时,需综合考虑抗风需求、施工条件、施工风险和经济性;(4)本研究成果可为大跨度斜拉桥临时抗风措施的选择提供参考。

采用改进最大相关熵自适应迭代容积卡尔曼滤波算法的锂离子电池荷电状态估计

针对非高斯噪声干扰下传统滤波算法在估计锂离子电池荷电状态(SOC)时存在不稳定以及精度低的问题,提出一种改进的最大相关熵自适应迭代容积卡尔曼滤波(IMCC-AICKF)算法,用于估计锂离子电池荷电状态。所提算法将加权最小二乘方法与最大相关熵准则(MCC)相结合,定义了一种新的代价权函数作为优化准则,通过优化噪声最小协方差矩阵来减小滤波误差,保证长时间滤波的收敛性和稳定性;再与自适应迭代容积卡尔曼滤波(AICKF)算法相结合,对过程噪声协方差和测量噪声协方差进行更新来提高估计的准确性和鲁棒性。基于两种电池数据,在非高斯噪声干扰下,运用所提算法对电池SOC进行估计,仿真结果表明:与容积卡尔曼滤波(CKF)算法和最大相关熵容积卡尔曼滤波(IMCC-CKF)算法相比,IMCC-AICKF算法对荷电状态估计的最大绝对误差、平均绝对误差和均方根误差都是最小的,且平均绝对误差和均方根误差均小于1%;在给定初始值错误的情况下,IMCC-AICKF算法可以准确收敛到真实值,具有较好的鲁棒性。所提算法在非高斯噪声下能实现更准确的估计,是一种估计精度高且鲁棒性好的SOC估计方法。

贵州威宁对流单体雷达回波分层结构特征分析

本文选取了2017—2020年威宁县111个对流单体(35个冰雹云单体和76个雷雨云单体),着重分析了对流单体雷达回波在垂直指向上的分层结构特征,并结合双偏振雷达观测分析了对流云单体偏振参量和水凝物相态分布特征。研究分析结果表明:①威宁对流单体雷达回波典型特征量基本一致,对流单体生命史周期约为100 min,最大反射率因子主要位于与0℃层高度差±2.0 km的范围内;②当对流单体雷达回波强度从45 dBz发展到55 dBz以上时,冰雹云具有发展迅速且持续时间长的特点,冰雹大小则与强回波在融化层高度以上的扩展高度存在一定的对应关系,高度越高、冰雹越大;③X波段双偏振天气雷达能够较好地反映降水粒子类型,基本符合粒子形状、大小和相态分布的特点,但应考虑降水相态粒子处于临界过渡区域的转化特点;④威宁多小冰雹主要与垂直风切变较弱、对流有效位能CAPE值不稳定能量偏低,且中小冰雹在下落过程中逐渐融化变小有关。

一种10 kV/10 ns/20 A全固态脉冲源设计

为获得等离子体研究所需的半高宽约10 ns的高压高重复频率脉冲输出,采用金属氧化物半导体场效应晶体管(MOSFET)开关串联构成的2组高压开关模块,利用传统电容储能脉冲产生电路和脉冲切尾电路相结合产生窄脉冲。结合开关实际工作需求,开展了窄脉冲产生电路适应性设计及仿真优化;依据优化结果,搭建窄脉冲产生电路实验装置。经测试,在500Ω负载上获得了峰值电压约10 kV、半高宽约10 ns、前沿约6 ns的脉冲输出。

基于事件触发加密的配电网预测辅助状态估计

电力信息-物理系统背景下,配电网的通信链路相较于输电网更易遭受到信息攻击。现有考虑信息攻击的状态估计方法中,检测-修正方法过度依赖于攻击检测,而抗差估计方法将信息攻击粗略视作量测异常值,信息攻击下的状态估计性能需进一步提高。为此,提出了一种基于事件触发加密的配电网预测辅助状态估计方法,旨在增强配电网状态估计应对信息攻击的主动防御能力并保证状态估计的性能。首先,构建事件触发加密传输框架以提高配电网状态估计应对信息攻击的主动防御能力。然后,针对事件触发加密传输框架带来的量测误差分布未知性,设计了一种基于柯西核函数的增强最大相关熵容积卡尔曼滤波算法,利用状态预测值辅助鲁棒滤波以实现未知量测噪声分布下的状态准确估计。最后,在改进的IEEE 33节点和IEEE 118节点配电系统上进行仿真分析以验证所提算法的有效性。

含LCC/MMC交直流混联系统的状态估计及不良数据检测

基于调度系统导出的通用信息模型(common information model,CIM)中的XML和E文档,从数据生成的角度出发,首先将导出文档转化为状态估计原始输入数据,考虑交流系统与电网换相换流器(line commutated converter,LCC)、模块化多电平换流器(modular multilevel converter,MMC)以及LCC与MMC间的相互影响,采用统一迭代法对500kV子网络进行交直流状态估计建模;其次,在原始量测数据的基础上施加高斯噪声,借助最大化残差检验方法以进行不良数据的检测与辨识;最后,通过仿真数据验证了交直流状态估计模型及不良数据检测与辨识的有效性。