Load Shedding Strategy Based on Combined Feed-Forward Plus Feedback Control over Data Streams

In data stream management systems (DSMSs), how to maintain the quality of queries is a difficult problem because both the processing cost and data arrival rates are highly unpredictable. When the system is overloaded, quality degrades significantly and thus load shedding becomes necessary. Unlike processing overloading in the general way which is only by a feedback control (FB) loop to obtain a good and stable performance over data streams, a feedback plus feed-forward control (FFC) strategy is introduced in DSMSs, which have a good quality of service (QoS) in the aspects of miss ratio and processing delay. In this paper, a quality adaptation framework is proposed, in which the control-theory-based techniques are leveraged to adjust the application behavior with the considerations of the current system status. Compared to previous solutions, the FFC strategy achieves a good quality with a waste of fewer resources.

Research in Control Systems, Sensor Fusion, and Haptic Interfaces

Research in control systems, sensor fusion and haptic interfaces is reviewed.

Lift fin stabilizers based on data fusion with wavelet denoising technology

Fin stabilizers with fin-lift feedback control can shield the mapping error of calculation between the fin angle and fin lift force,which is in the fin stabilizer with fin-angle feedback control.In practice,there are some technical difficulties in lift fin stabilizers,such as lift force detection and lift force sensor installation,so it cannot achieve the good antirolling performance.Therefore,a fin stabilizer system with fin-lift/fin-angle integrated control is brought forward.Data fusion based on wavelet denoising technology is employed in the system,which combines lift with fin angle local information from two sensors with different frequency ranges in order to eliminate redundant and contradictory information,and using complementary information to obtain the relative integrity of the lift force signal.The system model is established in this paper,and the fusion signal and the antirolling performance of this model are simulated respectively.The result shows that the control system can meet the antirolling need in different sea situations.

Detection and Defense Method Against False Data Injection Attacks for Distributed Load Frequency Control System in Microgrid

In the realm of microgrid(MG),the distributed load frequency control(LFC)system has proven to be highly susceptible to the negative effects of false data injection attacks(FDIAs).Considering the significant responsibility of the distributed LFC system for maintaining frequency stability within the MG,this paper proposes a detection and defense method against unobservable FDIAs in the distributed LFC system.Firstly,the method integrates a bi-directional long short-term memory(Bi LSTM)neural network and an improved whale optimization algorithm(IWOA)into the LFC controller to detect and counteract FDIAs.Secondly,to enable the Bi LSTM neural network to proficiently detect multiple types of FDIAs with utmost precision,the model employs a historical MG dataset comprising the frequency and power variances.Finally,the IWOA is utilized to optimize the proportional-integral-derivative(PID)controller parameters to counteract the negative impacts of FDIAs.The proposed detection and defense method is validated by building the distributed LFC system in Simulink.

Oracle数据库装载外部数据工具SQL*Loader的应用

Oracle数据库管理系统的SQL*Loader工具提供了将外部数据文件中的数据装载到数据库表中的有效手段。文中阐述了SQL*Loader完成的主要功能、工作机制及组件,对控制文件的语法结构及常用参数进行了较详细的论述,最后通过一个实例说明了装载数据的操作过程及方法。

Oracle数据库装载外部数据工具SQL*Loader的应用

Oracle数据库管理系统的SQL*Loader工具提供了将外部数据文件中的数据装载到数据库表中的有效手段。文中阐述了SQL*Loader完成的主要功能、工作机制及组件,对控制文件的语法结构及常用参数进行了较详细的论述,最后通过一个实例说明了装载数据的操作过程及方法。

Flexible substructure online hybrid test system using conventional testing devices

This paper presents a substructure online hybrid test system that is extensible for geographically distributed tests. This system consists of a set of devices conventionally used for cyclic tests to load the tested substructures onto the target displacement or the target force. Due to their robustness and portability, individual sets of conventional loading devices can be transported and reconfigured to realize physical loading in geographically remote laboratories. Another appealing feature is the flexible displacement-force mixed control that is particularly suitable for specimens having large disparities in stiffness during various performance stages. To conduct a substructure online hybrid test, an extensible framework is developed, which is equipped with a generalized interface to encapsulate each substructure. Multiple tested substructures and analyzed substructures using various structural program codes can be accommodated within the single framework, simply interfaced with the boundary displacements and forces. A coordinator program is developed to keep the boundaries among all substructures compatible and equilibrated. An Interuet-based data exchange scheme is also devised to transfer data among computers equipped with different software environments. A series of online hybrid tests are introduced, and the portability, flexibility, and extensibility of the online hybrid test system are demonstrated.

Study on Federated Architecture for GPS/INS/TRN Integrated Navigation System

Based on the information fusion theory, a kind of integrated navigation system integration for cruise missile is presented in this paper. Besides, the way with which the system is integrated and the related data fusion technique are discussed. Information-fusion-based hybrid navigation system integration can fully utilize information provided by all kinds of navigation sensor subsystem and can improve the precision of the system effectively. Simultaneously, the reconstructing ability ensures the system of great reliability.

Detection and Estimation of False Data Injection Attacks for Load Frequency Control Systems

False data injection attacks(FDIAs)against the load frequency control(LFC)system can lead to unstable operation of power systems.In this paper,the problems of detecting and estimating the FDIAs for the LFC system in the presence of external disturbances are investigated.First,the LFC system model with FDIAs against frequency and tie-line power measurements is established.Then,a design procedure for the unknown input observer(UIO)is presented and the residual signal is generated to detect the FDIAs.The UIO is designed to decouple the effect of the unknown external disturbance on the residual signal.After that,an attack estimation method based on a robust adaptive observer(RAO)is proposed to estimate the state and the FDIAs simultaneously.In order to improve the performance of attack estimation,the H¥technique is employed to minimize the effect of external disturbance on estimation errors,and the uniform boundedness of the state and attack estimation errors is proven using Lyapunov stability theory.Finally,a two-area interconnected power system is simulated to demonstrate the effectiveness of the proposed attack detection and estimation algorithms.

Data acquisition,analysis and applications of multi-sensor integration

This paper presents some key techniques for multi-sensor integration system, which is applied to the intelligent transportation system industry and surveying and mapping industry, e.g. road surface condition detection, digital map making. The techniques are synchronization control of multi-sensor, space-time benchmark for sensor data, and multi-sensor data fusion and mining. Firstly, synchronization control of multi-sensor is achieved through a synchronization control system which is composed of a time synchronization controller and some synchronization sub-controllers. The time synchronization controller can receive GPS time information from GPS satellites, relative distance information from distance measuring instrument and send space-time information to the synchronization sub-controller. The latter can work at three types of synchronization mode, i.e. active synchronization, passive synchronization and time service synchronization. Secondly, space-time benchmark can be established based on GPS time and global reference coordinate system, and can be obtained through position and azimuth determining system and synchronization control system. Thirdly, there are many types of data fusion and mining, e.g. GPS/Gyro/DMI data fusion, data fusion between stereophotogrammetry and PADS, data fusion between laser scanner and PADS, and data fusion between CCD camera and laser scanner. Finally, all these solutions presented in paper have been applied to two areas, i.e. land-bone intelligent road detection and measurement system and 3D measurement system based on unmanned helicopter. The former has equipped some highway engineering Co. , Ltd. and has been successfully put into use. The latter is an ongoing resealch.

Performance evaluation of sensor allocation algorithm based on covariance control

The covariance control capability of sensor allocation algorithms based on covariance control strategy is an important index to evaluate the performance of these algorithms. Owing to lack of standard performance metric indices to evaluate covariance control capability, sensor allocation ratio, etc, there are no guides to follow in the design procedure of sensor allocation algorithm in practical applications. To meet these demands, three quantified performance metric indices are presented, which are average covariance misadjustment quantity （ACMQ）, average sensor allocation ratio （ASAR） and matrix metric influence factor （MMIF）, where ACMQ, ASAR and MMIF quantify the covariance control capabili- ty, the usage of sensor resources and the robustness of sensor allocation algorithm, respectively. Meanwhile, a covariance adaptive sensor allocation algorithm based on a new objective function is proposed to improve the covariance control capability of the algorithm based on information gain. The experiment results show that the proposed algorithm have the advantage over the preceding sensor allocation algorithm in covariance control capability and robustness.

Data fusion and simulation-based planning and control in cyber physical system for digital assembly of aeroplane

This paper introduces a CPS application for intelligent aeroplane assembly.At first,the CPS structure is presented,which acquires the characteristics of general CPS and enables“simulation-based planning and control”to achieve high level intelligent assembly.Then the paper puts forward data fusion estimation algorithm under synchronous and asynchronous sampling,respectively.The experiment shows that global optimal distributed fusion estimation under synchronized sampling proves to be closer to the actual value compared with ordinary weighted estimation,and multi-scale distributed fusion estimation algorithm of wavelet under asynchronous sampling does not need time registration,it can also directly link to data,and the error is smaller.This paper presents hybrid control strategy under the circumstance of joint action of the inner and outer loop to address the problems caused by the less controllable feature of the parallel mechanism when undertaking online process simulation and control.A robust adaptive sliding mode controller is designed based on disturbance observer to restrain inner interference and maintain robustness.At the same time,an outer collaborative trajectory planning is also designed.All the experiment results show the feasibility of above proposed methods.

Three Applications of V.3 Google Maps: Just for Display of Data, or Analysis as Well?

A question about the analytical capability of Google maps is answered for three examples of pin maps, and polyline and polygon maps that are computer-programmed with the third version of the Google maps application. One map reads XML data stored on the home server, whereas another downloads its data from an online fusion table, and the third includes pre-programmed data. Each map permits users to query mashup layers after the map has loaded. However, an analytical capability comparable to GIS should require users to have access to their data for analysis with their own functions while the map is loading. The technical constraint of asynchronous loading of data for Google maps is illustrated for each map. In conclusion, only one map has an analytical capability that is achieved by means of deprecated synchronous loading of data.

A Dual-spline Approach to Load Error Repair in a HEMS Sensor Network

In a home energy management system(HEMS),appliances are becoming diversified and intelligent,so that certain simple maintenance work can be completed by appliances themselves.During the measurement,collection and transmission of electricity load data in a HEMS sensor network,however,problems can be caused on the data due to faulty sensing processes and/or lost links,etc.In order to ensure the quality of retrieved load data,different solutions have been presented,but suffered from low recognition rates and high complexity.In this paper,a validation and repair method is presented to detect potential failures and errors in a domestic energy management system,which can then recover determined load errors and losses.A Kernel Extreme Learning Machine(K-ELM)based model has been employed with a Radial Basis Function(RBF)and optimised parameters for verification and recognition;whilst a Dual-spline method is presented to repair missing load data.According to the experiment results,the method outperforms the traditional B-spline and Cubic-spline methods and can effectively deal with unexpected data losses and errors under variant loss rates in a practical home environment.

Fuzzy Self-adaptive Proportional Integration Differential Control for Attitude Stabilization of Quadrotor UAV

The technology of attitude control for quadrotor unmanned aerial vehicles(UAVs) is one of the most important UAVs' research areas.In order to achieve a satisfactory operation in quadrotor UAVs having proportional integration differential(PID) controllers,it is necessary to appropriately adjust the controller coefficients which are dependent on dynamic parameters of the quadrotor UAV and any changes in parameters and conditions could affect desired performance of the controller.In this paper,combining with PID control and fuzzy logic control,a kind of fuzzy self-adaptive PID control algorithm for attitude stabilization of the quadrotor UAV was put forward.Firstly,the nonlinear model of six degrees of freedom(6-DOF) for quadrotor UAV is established.Secondly,for obtaining the attitude of quadrotor,attitude data fusion using complementary filtering is applied to improving the measurement accuracy and dynamic performance.Finally,the attitude stabilization control simulation model of the quadrotor UAV is build,and the self-adaptive fuzzy parameter tuning rules for PID attitude controller are given,so as to realize the online self-tuning of the controller parameters.Simulation results show that comparing with the conventional PID controller,this attitude control algorithm of fuzzy self-adaptive PID has a better dynamic response performance.

An Adaptive Data Aggregation Algorithm in Wireless Sensor Network with Bursty Source

The Wireless Sensor network is distributed event based systems that differ from conventional communica-tion network. Sensor network has severe energy constraints, redundant low data rate, and many-to-one flows. Aggregation is a technique to avoid redundant information to save energy and other resources. There are two types of aggregations. In one of the aggregation many sensor data are embedded into single packet, thus avoiding the unnecessary packet headers, this is called lossless aggregation. In the second case the sensor data goes under statistical process (average, maximum, minimum) and results are communicated to the base station, this is called lossy aggregation, because we cannot recover the original sensor data from the received aggregated packet. The number of sensor data to be aggregated in a single packet is known as degree of ag-gregation. The main contribution of this paper is to propose an algorithm which is adaptive to choose one of the aggregations based on scenarios and degree of aggregation based on traffic. We are also suggesting a suitable buffer management to offer best Quality of Service. Our initial experiment with NS-2 implementa-tion shows significant energy savings by reducing the number of packets optimally at any given moment of time.

图书馆智慧管理平台书目数据融合若干问题分析——以河海大学图书馆为例

文章通过分析河海大学图书馆智慧管理平台下的书目数据融合项目的实践,总结了数据库中书目数据存在的问题及原因,从编目人员、编目外包公司、图书馆自身3个维度提出优化策略,以提升图书馆的编目业务的质量,促进图书馆编目事业稳定健康的发展。

综掘工作面风流调控下风速及瓦斯粉尘浓度融合预测模型研究

针对综掘工作面传统的通风总量控制管理模式不能根据实际需求进行风流调控,造成瓦斯及粉尘聚集和污染隐患等问题,对风流调控下的风速及瓦斯粉尘浓度多源数据融合神经网络预测模型进行了研究。采用欧拉-拉格朗日法建立了风流调控下的瓦斯及粉尘气固耦合模型并进行了测试验证,模拟分析瓦斯和粉尘颗粒在综掘巷道的分布情况,获取大量不同风流调控方案下的风速及瓦斯粉尘浓度样本数据。采用多层感知器神经网络技术建立预测模型结构,选取对瓦斯及粉尘浓度具有较大影响的风流调控等参数作为输入层,根据风速及瓦斯粉尘的隐患位置确定输出层,对样本数据进行预处理,通过引入差分进化算法搜索最佳隐藏层节点数和学习率,利用TensorFlow框架搭建多源数据融合神经网络预测模型。以陕北某矿综掘工作面为研究对象,对不同风流调控方案进行预测和井下实测验证。结果表明:该模型相对误差最大值为9.7%,具有较高的准确性;选取出风口距端头最短距离5 m和最远距离10 m这2种工况下的最佳调控方案,与调控前相比,风速符合规范要求,端头死角区瓦斯体积分数分别降低34%和35%,回风侧人行处平均粉尘质量浓度分别降低40%和41%,司机处粉尘质量浓度分别降低38%和36%,研究可为风流调控提供参考。

基于模糊理论的输电网络电压无功控制策略

为解决新能源、电动汽车、储能等新技术应用下,高复杂度电力系统电压稳定控制问题,提出了一种基于模糊理论的输电网络电压无功控制策略。该方法引入模糊理论中的隶属度函数,根据系统节点与不同分区之间的耦合程度制定无功控制策略。根据灵敏度计算网络各个节点之间的电气距离,通过模糊聚类算法对节点进行初步分区,并采用聚类融合算法对聚类产生的多个结果进行融合,从而得到最终分区结果。根据关键节点对各个分区的隶属度制定主辅控制策略。IEEE30节点输电网络的算例分析表明,该控制策略可以有效实现对无功功率的控制。

降雨监测与预报技术在防洪减灾中的应用进展

洪水灾害突发性强,成灾速度快,对人民生命和财产安全造成较大的威胁。降雨作为洪水灾害致灾因子,数据的精确度对防洪减灾具有重要意义。以降雨监测与预报技术为切入点,对雨量站点观测、天气雷达降雨估计及预报、降雨数值预报、卫星遥感反演的现状进行了总结,通过分析时空降尺度方法及多源数据融合技术在降雨监测与预报中的应用,揭示了其在提升降雨数据“量”与“型”准确度方面的效果。研究表明:降雨监测与预报技术在当前取得了显著进展,但在山丘区和城市环境空间的复杂地形方面仍面临分辨率受到限制及精确性、时效性不足的问题。多源数据融合能提高降雨数据精度、时空覆盖能力和预测准确性,优化算法模型、融合“空-天-地”多源数据形成高分辨率预报是未来的研究方向。