GPS动态定位中自适应卡尔曼滤波模型的建立及其算法研究

采用描述机动载体运动的“当前”统计模型，建立了一种新的ＧＰＳ动态定位自适应卡尔曼滤波模型。为了进一步提高滤波器的动态性能，提出一种改进的自适应滤波算法，大大提高了ＧＰＳ动态定位卡尔曼滤波器的跟踪能力，改善了滤波效果。计算机仿真结果验证了该算法的有效性。     

现代船舶动力定位系统设计

围绕现代动力定位系统的设计问题,讨论系统的构建、数学建模、控制器设计和推力器的推力分配,重点给出了基于扩展Kalman滤波的动力定位LQG控制器设计算法。     

基于实数遗传算法的列车优化操纵曲线研究

列车优化操纵是列车节能控制的关键问题，以列车运行动力学方程和牵引计算理论为基础，结合列车运行过程中的要求，构建以能耗、时分误差、限速等为目标的列车节能控制模型，采用实数遗传算法，通过Visual Basic编程对此问题进行求解。在已知列车编组的条件下，以DF4型内燃机车牵引客车、空气制动和燃油量曲线为基础，得到给定运行时间、距离条件下的优化操纵曲线，从而对司机操纵给出指导性意见。     

小波变换在管道泄漏点定位中的应用

当管道发生泄漏时，泄漏诱发的负压波传播到管道上下游监测点时会使该点压力信号幅值产生瞬态下降，利用小波变换模极大值检测压力信号的突变点，从而计算出管道泄漏诱发的负压波传播到上下游监测点的时间差。在MATLAB6．1软件环境下，以某次实验数据为例进行管道泄漏点定位研究。在计算过程中小波基函数选取为Haar小波，尺度水平为6，计算结果表明该方法可以计算出管道泄漏点处诱发的负压波传播到管道上游监测点的时间差，从而为准确定位泄漏点提供了基础。     

Large-scale evacuation network optimization: a bi-level control method with uncertain arterial demand

To improve the efficiency of large-scale evacuations, a network aggregation method and a bi-level optimization control method are proposed in this paper. The network aggregation method indicates the uncertain evacuation demand on the arterial sub-network and balances accuracy and efficiency by refining local road sub-networks. The bi-level optimization control method is developed to reconfigure the aggregated network from both supply and demand sides with contraflow and conflict elimination. The main purpose of this control method is to make the arterial sub-network to be served without congestion and interruption. Then, a corresponding bi-objective network flow model is presented in a static manner for an oversaturated network, and a Genetic Algorithm-based solution method is used to solve the evacuation problem. The numerical results from optimizing a city-scale evacuation network for a super typhoon justify the validity and usefulness of the network aggregation and optimization control methods.     

基于改进BP-GA方法的FPSO舷侧结构耐撞性能优化设计

基于遗传算法和ABAQUS参数化有限元仿真技术,对传统的BP-GA优化方法进行改进,并采用改进的BP-GA方法对浮式生产储油卸油装置(FPSO)舷侧结构的耐撞性能进行优化,以验证其可行性和准确性。结果表明,与传统的BP神经网络相比,经遗传算法优化的BP神经网络具有更高的预测精度和更强的泛化能力;改进的BP-GA优化方法可在结构减重的基础上进一步提高结构的耐撞性能,能较好地适用于复杂的FPSO舷侧结构耐撞性优化设计。采用的优化方法具有通用性,可为抗爆性能的优化设计提供参考。     

Highway voting system: Embracing a possible paradigm shift in traffic data acquisition

The integration of internet and mobile phones has opened the door to a new wave of utilizing private vehicles as probes not only for performance evaluation but for traffic control as well, gradually replacing the role of traffic surveillance systems as the dominant source of traffic data. To prepare for such a paradigm shift, one needs to overcome some key institutional barriers, in particular, the privacy issue. A Highway Voting System (HVS) is proposed to address this issue in which drivers provide link- and/or path-based vehicle data to the traffic management system in the form of “votes” in order to receive favorable service from traffic control. The proposed HVS offers a platform that links data from individual vehicles directly with traffic control. In the system, traffic control responds to voting vehicles in a way similar to the current system responding to prioritized vehicles and providing the requested services accordingly. We show in the paper that the proposed “voting” system can effectively resolve the privacy issue which often hampers traffic engineers from getting detailed data from drivers. Strategies to entice drivers into “voting” so as to increase the market penetration level under all traffic conditions are discussed. Though the focus of the paper is on addressing the institutional issues associated with data acquisition from individual vehicles, other research topics associated with the proposed system are identified. Two examples are given to demonstrate the impact of the proposed system on algorithm development and traffic control.     

Dynamic demand estimation and prediction for traffic urban networks adopting new data sources

Nowadays, new mobility information can be derived from advanced traffic surveillance systems that collect updated traffic measurements, both in fixed locations and over specific corridors or paths. Such recent technological developments point to challenging and promising opportunities that academics and practitioners have only partially explored so far.The paper looks at some of these opportunities within the Dynamic Demand Estimation problem (DDEP). At first, data heterogeneity, accounting for different sets of data providing a wide spatial coverage, has been investigated for the benefit of off-line demand estimation. In an attempt to mimic the current urban networks monitoring, examples of complex real case applications are being reported where route travel times and route choice probabilities from probe vehicles are exploited together with common link traffic measurements.Subsequently, on-line detection of non-recurrent conditions is being recorded, adopting a sequential approach based on an extension of the Kalman Filter theory called Local Ensemble Transformed Kalman Filter (LETKF).Both the off-line and the on-line investigations adopt a simulation approach capable of capturing the highly nonlinear dependence between the travel demand and the traffic measurements through the use of dynamic traffic assignment models. Consequently, the possibility of using collected traffic information is enhanced, thus overcoming most of the limitations of current DDEP approaches found in the literature.     

基于模糊PID控制的ABS仿真研究

以车轮滑移率为控制对象,分析了模糊控制的理论基础,将传统的模糊控制与经典的PID控制相结合,提出了白适应模糊PID控制算法,并进行了仿真研究.     

基于双轴位置转台的捷联惯导系统级标定技术

本文研究一种基于双轴位置转台的激光陀螺捷联惯导系统的系统级标定方法。建立了附加约束条件的陀螺和加速度计标定模型,从捷联惯导系统的误差方程出发,建立30维Kalman滤波标定模型,以速度和位置作为观测量,并设计双轴位置旋转路径,对惯性仪表标定参数进行激励与辨识。仿真实验结果表明,该方法能够准确估计出陀螺和加速度计的15个标定误差参数,具有一定的参考价值。