Fault tolerant nonlinear control with applications to an automated transit bus

This paper presents an integrated structure for a passive and active fault tolerant control (FTC) design approach in the framework of a robust nonlinear control technique called Dynamic Surface Control (DSC). As motivated by the automated vehicle application, we consider two categories of possible faults: pre-specified (a priori) and non-specified faults. It is first shown that DSC can be considered as a passive FTC approach in the sense that it gives simultaneous robust stability to a set of nonlinear systems even in the presence of model uncertainties and the pre-specified faults. Then, the non-specified fault is classified depending on the fault’s impact on the closed-loop system and isolatability from a fault detection and diagnosis (FDD) system. If a fault is both intolerable and isolatable, an active FTC approach is taken which includes FDD and controller reconfiguration. More specifically, trajectory reconfiguration is considered to accommodate the actuator fault, i.e., to compensate for the performance loss due to the fault within the framework of a switched hierarchical structure. Finally, the integrated structure for the longitudinal control of an automated transit bus is designed through the proposed method. Simulation results of the fault tolerant controller are shown for both single and multiple multiplicative faults. This controller was implemented on the California PATH transit buses in a demonstration of automated public transportation technology in San Diego, California in August of 2003.     

紧急疏散情况下地铁车站动态瓶颈识别

随着城市轨道交通系统逐渐成网,地铁车站日渐拥挤,为了制定科学有效的紧急疏散方案,有必要预先找到车站瓶颈点。基于时间可靠度函数模拟乘客在紧急情况下路径选择行为,在此基础上引入M//G/C/C排队模型对车站排队系统各个服务台进行排队性能指标计算,找出潜在瓶颈点。以广州地铁3号线岗顶站为例,结合车站硬件设施尺寸数量,模拟计算最恶劣情况下乘客疏散过程,找到3处潜在瓶颈点,测算结果与实际观测情况相符合,验证了该方法的有效性。     

拖船操纵运动与水下拖曳列阵的耦合运动分析

建立了拖船操纵运动与水下拖曳列阵的三维非线性数学模型,求解了在脐带非线性缆力作用下的运动方程,模拟了拖曳系统在几种典型状态下其缆索的形态变化,以及列阵张力变化。     

Ant Colony Routing algorithm for freeway networks

Dynamic traffic routing refers to the process of (re)directing vehicles at junctions in a traffic network according to the evolving traffic conditions. The traffic management center can determine desired routes for drivers in order to optimize the performance of the traffic network by dynamic traffic routing. However, a traffic network may have thousands of links and nodes, resulting in a large-scale and computationally complex non-linear, non-convex optimization problem. To solve this problem, Ant Colony Optimization (ACO) is chosen as the optimization method in this paper because of its powerful optimization heuristic for combinatorial optimization problems. ACO is implemented online to determine the control signal – i.e., the splitting rates at each node. However, using standard ACO for traffic routing is characterized by four main disadvantages: 1. traffic flows for different origins and destinations cannot be distinguished; 2. all ants may converge to one route, causing congestion; 3. constraints cannot be taken into account; and 4. neither can dynamic link costs. These problems are addressed by adopting a novel ACO algorithm with stench pheromone and with colored ants, called Ant Colony Routing (ACR). Using the stench pheromone, the ACR algorithm can distribute the vehicles over the traffic network with less or no traffic congestion, as well as reduce the number of vehicles near some sensitive zones, such as hospitals and schools. With colored ants, the traffic flows for multiple origins and destinations can be represented. The proposed approach is also implemented in a simulation-based case study in the Walcheren area, the Netherlands, illustrating the effectiveness of the approach.     

A bi-objective dynamic programming approach for airline green fleet planning

Ensuring a fleet of green aircraft is a basic step in mitigating aviation pollution issues that are expected to be worsen in the coming years due to rapid air traffic growth. This study proposed a novel methodology in green fleet planning in which both profit and green performance of airline are considered simultaneously and explicitly. To do this, a Green Fleet Index (GFI) is derived as an indicator to quantify the green performance of airline’s fleet. It measures the degree of airline compliance with a standard requirement in terms of emission, noise, and fuel consumption. A bi-objective dynamic programming model is then formulated to find optimal aircraft acquisition (lease or purchase) decision by minimizing GFI and maximizing profit. Several interesting results are obtained: (1) considering environmental issue as secondary objective yields a greener fleet; (2) airline’s profit is affected, but could be recovered from environmental cost savings; (3) increasing load factor is an effective operational improvement strategy to enhance airline’s green performance and raise profit level. It is anticipated that the framework developed in this study could assist airlines to make a smart decision when considering the need to be green.     

高速铁路5×50m钢箱-混凝土连续结合梁设计研究

连续结合梁作为将钢与混凝土相组合共同参与工作的体系,受力十分复杂,应用中要确保结构具有良好的静力、动力性能。以某高速铁路5×50 m钢箱-混凝土连续结合梁为工程背景,介绍设计时对负弯矩区处理、桥面板预应力施加、混凝土徐变和活载效应、动力性能等重点问题的计算和分析,研究表明,通过调整施工顺序、采用合理的徐变及活载计算方法、底板铺设混凝土等措施,可使结构各项指标满足要求。     

不断轨动态称量轨道衡安装导引

从轨道衡地点选定、线路要求、机械台而、电气设备等方面介绍不断轨动态称量轨道衡安装各阶段、过程的方法与指引，以及轨道衡的计量检定。     

汽车生产企业如何构建DFMEA平台

随着全球化进程的推进,制定一个国际通用的汽车行业质量管理体系认证标准已经成为广大汽车生产厂家的共同呼声,在此背景下,ISO/TS16949在1999年应运而生。经过适应性更改,2003年ISO/TS16949:2002正式发布并沿用至今。五大工具是ISO/TS16949:2002推荐的产品策划、过程控制、实现预防为主及其测量系统评定的重要手段,是集世界汽车制造企业专家管理经验之大成而总结的产品质量管理方法,其在企业生产经营的过程中表现出来的质量控制的有效性已经经过实践再三检验。五大工具之一——设计潜在失效模式及后果分析(DFMEA)是ISO/TS16949:2002推荐的实现预防为主的重要手段。应用DFMEA可以识别、评价产品设计中潜在的失效及其后果,找到能够避免或减少这些潜在失效发生的措施。将这些分析过程文件化,这是对设计过程的完善。成功实施DFMEA的重要因素之一是及时性,它是一个"事前的行为",而不是"事后的处置",为达到最佳效益,DFMEA必须在产品设计失效模式被纳入到产品设计之前进行。ISO/TS16949:2002中有大小15个条款涉及DFMEA,其质量控制思想贯穿于TS16949标准全过程。如何快速应用DFMEA工具,在汽车产品设计过程中有效的进行质量控制,成为各大汽车生产厂家应该重点关注的问题。     

动态信号采集分析仪(CY-1型)系统及原理

介绍了动态信号采集分析仪（CY-1型）的原理。该系统适用于多种物理模型试验，如船舶性能、船舶在风浪流自然载荷条件下对港口设施的影响（码头受到的撞击力与缆绳受到的拉力等）、桥墩防撞设施以及水工结构物等。实践表明，该系统精度高且操作方便，所以在物理模型试验中是不可或缺的。最后指出了可进一步完善该系统的若干方法。     

Simulation of dynamic interaction between train and railway turnout

Dynamic train–track interaction is more complex in railway turnouts (switches and crossings) than that in ordinary tangent or curved tracks. Multiple contacts between wheel and rail are common, and severe impact loads with broad frequency contents are induced, when nominal wheel–rail contact conditions are disturbed because of the continuous variation in rail profiles and the discontinuities in the crossing panel. The absence of transition curves at the entry and exit of the turnout, and the cant deficiency, leads to large wheel–rail contact forces and passenger discomfort when the train is switching into the turnout track. Two alternative multibody system (MBS) models of dynamic interaction between train and a standard turnout design are developed. The first model is derived using a commercial MBS software. The second model is based on a multibody dynamics formulation, which may account for the structural flexibility of train and track components (based on finite element models and coordinate reduction methods). The variation in rail profile is accounted for by sampling the cross-section of each rail at several positions along the turnout. Contact between the back of the wheel flange and the check rail, when the wheelset is steered through the crossing, is considered. Good agreement in results from the two models is observed when the track model is taken as rigid.