Assimilation of altimetric data in the mid-latitude oceans using the Singular Evolutive Extended Kalman filter with an eddy-resolving, primitive equation model

A new data assimilation scheme has been elaborated for ocean circulation models based on the concept of an evolutive, reduced-order Kalman filter. The dimension of the assimilation problem is reduced by expressing the initial error covariance matrix as a truncated series of orthogonal perturbations. This error sub-space evolves during the assimilation so as to capture the growing modes of the estimation error. The algorithm has been formulated in quite a general fashion to make it tractable with a large variety of ocean models and measurement types. In the present paper, we have examined three possible strategies to compute the evolution of the error subspace in the so-called Singular Evolutive Extended Kalman (SEEK) filter: the steady filter considers a time-independent error sub-space, the apprentice filter progressively enriches the error sub-space with the information learned from the innovation vector after each analysis step, and the dynamical filter updates the error sub-space according to the model dynamics. The SEEK filter has been implemented to assimilate synthetic observations of the surface topography in a non-linear, primitive equation model that uses density as vertical coordinate. A simplified box configuration has been adopted to simulate a Gulf Stream-like current and its associated eddies and gyres with a resolution of 20 km in the horizontal, and 4 levels in the vertical. The concept of twin experiments is used to demonstrate that the conventional SEEK filter must be complemented by a learning mechanism in order to model the misrepresented tail of the error covariance matrix. An approach based on the vertical physics of the isopycnal model, is shown particularly robust to control the velocity field in deep layers with surface observations only. The cost of the method makes it a suitable candidate for large-size assimilation problems and operational applications.     

高速铁路车站电力谐波分析及抑制

介绍谐波的产生机理及主要分析方法,针对高速铁路车站存在的谐波污染问题,建立车站电力负荷谐波模型进行仿真分析,结合实际测量,得出铁路车站的谐波含量及特征。对铁路车站谐波进行超标率分析表明,按需滤除特征次数谐波设计的无源滤波器一般能够满足国标要求。含无源滤波功能的并联电容器组投切试验表明,合适的分组投切方式下,电容器组能够起到较好的谐波抑制效果。     

铁路牵引供电系统设计中的谐波谐振分析及抑制方案研究

为了避免交直交型电力机车(含动车组)与牵引供电系统之间形成谐波谐振,影响电气化铁路运行安全,有必要在牵引供电系统设计阶段开展谐波谐振特性分析。基于四象限变流器拓扑结构与控制策略,构建电力机车谐波源特性模型,针对某新建电气化铁路牵引供电系统设计方案,构建牵引供电系统数学模型,利用MATLAB/Simulink仿真平台,研究系统谐波谐振特性与变化规律,给出便于工程应用的滤波器设计方案,并验证该方案的可行性。     

中水脱氮实验研究

目前中水厂处理采用的基本工艺对去除污水中氮的效果不好,易造成水体富营养化。由于中水厂出水中氮的含量相对较低,属于微污染水,不适合采用化学方法进行去除,要去除这种水质中的氮考虑采用生物法脱氮。本项目先研究了在慢滤状态,陶粒生物慢滤池对氮的去除效果,继而改进实验装置在慢滤池后加入碎石曝气段及石英砂快滤段,有效地提高了氮的去除效果,氮的去除率基本上都在14％以上,最好时对氨氮去除率可达到28．57％以上。     

涡凹气浮联合固定化曝气生物滤池在含油废水中的应用

采用CAF联合BAF工艺处理高浓度炼油生产废水,并利用浮动环流收油器,对预处理废水中的油类污染物进行回收,无需外加压力,处理成本低。经该工艺二级气浮处理后,油类污染物回收率达到97％。工艺调试运行稳定后,对污染物COD、氨氮、硫化物和石油类进行监测。监测结果表明,COD、氨氮、硫化物和石油类污染物的去除率分别为：96．1％、94．3％、77％和96．7％,出水水质满足GB8978--1996《污水综合排放标准》中第二类污染物最高允许排放浓度一级标准要求。     

基于LCL滤波器的双馈风电网侧变换器不同控制结构性能研究

为分析基于LCL滤波器的双馈风电网侧变换器在不同电流反馈控制结构情况下的工作性能,采取PI控制器对网侧变换器网侧电流反馈控制结构和变换器侧电流反馈控制结构的电流闭环根轨迹进行分析,对其在理想电网无阻尼电阻和有阻尼电阻、非理想电网无阻尼电阻3种情况下的特性进行了比较。分析及仿真结果表明变换器侧电流反馈控制结构控制算法相对较复杂,但是系统稳定性好,电网电流的谐波畸变率较低;而电网侧电流反馈控制结构较易实现网侧单位功率因数控制,但稳定性较差。     

基于单周期控制的统一电能质量调节器的设计

基于统一电能质量调节器（UPQC）对电能质量进行补偿时的同步性问题和控制的复杂性两个方面的考虑,在对UPQC拓扑结构与工作原理分析的基础上,提出了基于单周期控制的统一电能质量调节器控制策略,完成对UPQC中的DVR和APF两部分的同步控制,拓扑结构简单、易于实现。在理论分析的基础上,应用Simulink对单周期控制的统一电能质量系统进行了建模和仿真,仿真结果表明,该方法能在一个开关周期内消除稳态误差,证明了该拓扑的实用性和控制方法的有效性。     

基于LCL滤波器的电压型PWM整流器新型电流控制策略研究

在对基于LCL滤波器的三相电压型PWM整流器研究基础上提出了一种新型的电流控制策略。该策略采取了电网侧电流反馈控制,能够方便对功率因数进行控制。为了保证系统的稳定性,在电流环内引入了电网电流二次微分环节,根据二相静止坐标系下实轴和虚轴正弦函数的特性,在算法中避免了微分环节可能造成的高频噪声问题。对所提出的控制策略进行了分析和仿真,在此基础上搭建了以TMS320LF2407为控制核心的基于LCL滤波器的三相电压型PWM整流器系统。仿真和实验结果验证了该算法的可行性。     

Using the lead vehicle as preview sensor in convoy vehicle active suspension control

Both ride quality and roadholding of actively suspended vehicles can be improved by sensing the road ahead of the vehicle and using this information in a preview controller. Previous applications have used look-ahead sensors mounted on the front bumper to measure terrain beneath. Such sensors are vulnerable, potentially confused by water, snow, or other soft obstacles and offer a fixed preview time. For convoy vehicle applications, this paper proposes using the overall response of the preceding vehicle(s) to generate preview controller information for follower vehicles. A robust observer is used to estimate the states of a quarter-car vehicle model, from which road profile is estimated and passed on to the follower vehicle(s) to generate a preview function. The preview-active suspension, implemented in discrete time using a shift register approach to improve simulation time, reduces sprung mass acceleration and dynamic tyre deflection peaks by more than 50% and 40%, respectively. Terrain can change from one vehicle to the next if a loose obstacle is dislodged, or if the vehicle paths are sufficiently different so that one vehicle misses a discrete road event. The resulting spurious preview information can give suspension performance worse than that of a passive or conventional active system. In this paper, each vehicle can effectively estimate the road profile based on its own state trajectory. By comparing its own road estimate with the preview information, preview errors can be detected and suspension control quickly switched from preview to conventional active control to preserve performance improvements compared to passive suspensions.     

高速磁悬浮列车间隙信号数字滤波器设计与实现

分析了高速磁浮列车间隙信号噪声的特点,采用基于FPGA的FIR数字滤波器滤除噪声。应用基于位级联的多查找表分布式算法实现16阶低通FIR滤波器,由verilog-HDL语言完成设计文件,并在Simulink及ModelSim ISE 6.1平台上进行了试验仿真,结果均满足设计要求。