基于支持向量机模型的船舶航行广义预测控制

船舶操纵一直是船舶运动控制的研究重点,它与航行安全、能源节约和操作省力密切相关。模型是研究船舶运动控制的基础,本文鉴于船舶的动态具有大惯性、大时滞、非线性等特点,采用了基于结构风险最小化原则的神经网络———支持向量机对船舶进行建模,在建模中充分发挥支持向量机可以任意逼近非线性模型的良好特性,解决对船舶航向预测的问题。进而通过建立预测模型,并结合广义预测控制的算法达到航向保持的目的,且具有较好的稳定性和鲁棒性。     

基于涌水量预估和动态监测的公路隧道长距离反坡排水施工技术及其应用

常规的隧道反坡排水方案都是基于设计涌水量制定的,往往由于对涌水量判断不准确而导致排水能力不足或过剩,造成涌水灾害或资源配置浪费。为此,在"提前整体配置,过程局部优化"设计理念的基础上,提出基于涌水量预估和动态监测的隧道长距离反坡排水技术。该技术采用瞬变电磁、激发极化超前探测技术,对掌子面前方含水区位置及水量进行较准确的定位和预估;提出成本最小化排水优化公式,优化泵站分级设计及水泵功率选择;同时,动态监测涌水量,根据监测结果进行排水设置,提出了增级截流集水坑技术,有效解决2级泵站之间的排水问题。在宁夏东毛高速公路六盘山隧道中对该技术进行了应用,通过对反坡排水方案的优化,较好地完成了反坡排水任务,节约了排水成本,保证了隧道施工安全,取得了良好的应用效果。     

考虑异质性的经典随机后悔最小化模型改进研究

传统基于后悔理论的交通行为模型对异质性考虑不充分，对真实选择行为的解释存在不足.本文利用韦伯比率，考虑出行者对各方式属性变量感知的异质性，对经典随机后悔最小化模型进行改进，分别建立基于随机效用最大化，经典随机后悔最小化和改进经典随机后悔最小化的选择模型；以网约车选择行为为例进行实证研究，验证改进模型效果.结果表明：3种模型参数标定结果具有一致性，改进模型的拟合优度(0.271)和命中率(75.8%)相较于另外两个模型均较优；改进模型能更好地描述多维属性决策过程中的半补偿原则和折中效应，可以提高模型对真实选择行为的解释能力.     

Closing the loop in real-time railway control: Framework design and impacts on operations

Railway traffic is heavily affected by disturbances and/or disruptions, which are often cause of delays and low performance of train services. The impact and the propagation of such delays can be mitigated by relying on automatic tools for rescheduling traffic in real-time. These tools predict future track conflict based on current train information and provide suitable control measures (e.g. reordering, retiming and/or rerouting) by using advanced mathematical models. A growing literature is available on these tools, but their effects on real operations are blurry and not yet well known, due to the very scarce implementation of such systems in practice.In this paper we widen the knowledge on how automatic real-time rescheduling tools can influence train performance when interfaced with railway operations. To this purpose we build up a novel traffic control framework that couples the state-of-the art automatic rescheduling tool ROMA, with the realistic railway traffic simulation environment EGTRAIN, used as a surrogate of the real field. At regular times ROMA is fed with current traffic information measured from the field (i.e. EGTRAIN) in order to predict possible conflicts and compute (sub) optimal control measures that minimize the max consecutive delay on the network. We test the impact of the traffic control framework based on different types of interaction (i.e. open loop, multiple open loop, closed loop) between the rescheduling tool and the simulation environment as well as different combinations of parameter values (such as the rescheduling interval and prediction horizon). The influence of different traffic prediction models (assuming e.g. aggressive versus conservative driving behaviour) is also investigated together with the effects on traffic due to control delays of the dispatcher in implementing the control measures computed by the rescheduling tool.Results obtained for the Dutch railway corridor Utrecht–Den Bosch show that a closed loop interaction outperforms both the multiple open loop and the open loop approaches, especially with large control delays and limited information on train entrance delays and dwell times. A slow rescheduling frequency and a large prediction horizon improve the quality of the control measure. A limited control delay and a conservative prediction of train speed help filtering out uncertain traffic dynamics thereby increasing the effectiveness of the implemented measures.     

两层分级多学科设计框架在AUV的总体设计中的应用

将多学科优化方法作为一种新的设计方法应用于AUV的总体性能优化设计中.文中构建顶层控制系统层和并行独立子系统底层的两层分级的多学科优化设计框架,来实现AUV总体设计的有效载荷部分长度和推进力最大化和总重量最小化等的多个设计目标.使用的设计工具为商业软件iSIGHT和Fortran.     

船舶最小回转半径

本文确定了动稳定船舶的最小定常回转半径,进而就可把最优化方法应用于船舶操纵性设计中去。 基于线性化操纵运动方程,在优化过程中,把船体诸形状参数和舵面积作为设计变量,把回转性指数的倒数作为目标函数,把动稳定准则c′作为优化的约束条件。 根据计算结果,本文清晰地阐明了船体某些形状参数及舵面积的变化对最小回转半径的影响。     

随机交通网络中依赖信息的路径优化问题研究

针对交通网络中路径通行时间具有与时间相关的随机分布特性，将研究在此类交通网络上依赖信息的路径选择问题。在路径选择过程中引入交通信息，在随机交通网络上最优路径选择原则为下一节点的选择将依赖于已实现的路段时间及当前节点的出发时间，通过期望最小值方法，按照路径通行时间期望值最小原则，建立一种通过所获得交通信息来进行路径选择的优化模型，给出了模型的求解算法。并在简单交通网络上对模型进行实现。