铁道车辆横向能量回馈式主动悬挂鲁棒控制

为保证一类具有参数不确定的铁道车辆横向能量回馈式主动悬挂系统的稳定性, 通过引入带有交叉乘积项的二次型调节器, 提出了一种鲁棒H∞控制器的设计方法, 并对含摄动的悬挂系统模型进行了鲁棒H∞控制器设计。分析了具有参数摄动的能量回馈式主动悬挂系统的能量平衡条件, 并在MATLAB/SIMULINK下, 对控制系统进行了仿真。仿真结果表明: 不确定闭环系统的结构奇异值峰值为0.867 5, 鲁棒H∞控制器使得能量回馈式主动悬挂系统鲁棒稳定; 车辆模型的共振频率增益降低了40 dB, 悬挂减振性能得到明显改善; 整个仿真过程回收能量为29.5 J, 系统达到了能量平衡。     

应急设施鲁棒优化选址模型及算法

为解决不确定情况下应急设施选址问题, 采用鲁棒优化方法处理应急节点权重的区间估计, 基于最优的设施选址到各个应急节点的赋权距离之和最小, 建立有限期要求的不确定性应急设施选址模型, 并给出了模型的求解算法, 比较分析了鲁棒解与确定情况下的最优解。分析结果表明: 当情况发生变化后, 在确定情况下得到的最优解将发生较大的偏差, 而在所有可能发生的情况下, 鲁棒解与最优解目标函数值的最大偏差最小, 因此, 不确定性应急设施选址模型的解可以有效规避风险。     

铁路枢纽内快运班列车流组织的鲁棒优化研究

针对当前生产运营中较少考虑货运站点货物需求不确定性以及客户对货物运到期限的要求,设计双层时空服务网络描述枢纽内快运班列车流组织过程.该网络分为货源层和编组层,货源层中带有方向别的车流选择延迟弧或运输弧在相应时段到达编组层中的编组站.同时考虑编组站办理方向总数和车流组织基本约束,构建了铁路枢纽内快运班列车流组织鲁棒优化模型(CR),使用IBMILOG Cplex软件对模型进行精确求解.通过算例和大规模测试进行验证分析,结果表明,当ω=0.03时,鲁棒模型的目标函数值比随机优化模型(CS)的目标函数值降低5.10%,发送车数提高5.66%,最长求解时间为82 s,鲁棒性强于随机优化模型.虽然确定性模型(CD)在—些情景下可以获得较优的解,但是在需求不确定的条件下,确定性模型目标函数值要差于随机优化模型和鲁棒模型.当枢纽内货运站点数设为50时,时空网络服务弧段数达317,模型的求解时间为1 375.4 s,在可以接受的时间范围内.     

船舶航向保持的鲁棒神经网络控制

设计一个N5-5-5-5-5-5-1前向神经网络,经训练得到一个开环的船舶航向保持控制器,使其能够较好地保持典型输入信号作用下的船舶航向;然后应用闭环增益成形算法,形成闭环控制系统.这种基于神经网络的航向保持方案,将神经网络的适应能力、非线性函数映射能力和闭环增益成形算法的鲁棒性结合起来,改善了系统的鲁棒性能.这种方法设计过程简单,物理意义明显.     

Application of H∞ control in rudder/flap vector robust control of a ship＇s course

Given the uncertainty of parameters and the random nature of disturbances that effect a ships course, a robust course controller should be designed on the basis of rudder/flap vector control. This paper analyzes system uncertainty, and the choice of weighting functions is also discussed. When sea waves operate on a ship, the energy-concentrating frequency varies with the angle of encounter. For different angles of encounter, different weighting functions are designed. For the pole of a nominal model existing in an imaginary axis, the bilinear-transform method is used. The ＂2-Riccati＂ equation is adopted to solve the H∞ controller. A system simulation is given, and the results show that, compared with a PID controller, this system has higher course precision and more robust performance. This research has significant engineering value.     

基于容差模型的发动机悬置系统稳健优化设计

应用稳健优化设计理论,考虑设计变量的不确定性对结果的影响,建立稳健优化模型。以发动机悬置系统能量解耦为目标,用Pareto遗传算法对系统的刚度参数进行稳健优化,并将优化结果运用Monte Carlo方法进行分析.结果表明,优化方法可以有效提高悬置系统的稳健性。     

A New Robust Image Matching Method Based on Distance Reciprocal

Object matching between two-dimensional images is an important problem in computer vision. The purpose of object matching is to decide the similarity between two objects. A new robust image matching method based on distance reciprocal was presented. The distance reciprocal is based on human visual perception. This method is simple and effective. Moreover, it is robust against noise. The experiments show that this method outperforms the Hausdorff distance, when the images with noise interfered need to be recognized.     

Finding time‐robust fuel‐efficient paths for a call‐taxi in a stochastic city road network

Intra‐city commuting is being revolutionized by call‐taxi services in many developing countries such as India. A customer requests a taxi via phone, and it arrives at the right time and at the right location for the pick‐up. This mode of intra‐city travel has become one of the most reliable and convenient modes of transportation for customers traveling for business and non‐business purposes. The increased number of vehicles on city roads and raising fuel costs has prompted a new type of transportation logistics problem of finding a fuel‐efficient and quickest path for a call‐taxi through a city road network, where the travel times are stochastic. The stochastic travel time of the road network is induced by obstacles such as the traffic signals and intersections. The delay and additional fuel consumption at each of these obstacles are calculated that are later imputed to the total travel time and fuel consumption of a path. A Monte‐Carlo simulation‐based approach is proposed to identify unique fuel‐efficient paths between two locations in a city road network where each obstacle has a delay distribution. A multi‐criteria score is then assigned to each unique path based on the probability that the path is fuel efficient, the average travel time of the path and the coefficient of variation of the travel times of the path. Copyright © 2016 John Wiley & Sons, Ltd.     

基于航迹信息的舰船目标姿态角鲁棒估计

针对基于高分辨距离像的舰船目标识别中姿态角估计精度的问题,提出一种计算舰船目标运动姿态角的鲁棒性估计方法。该方法首先建立了目标姿态角估计模型,然后有针对性的对航迹数据的野值进行剔除,最后采用M-估计方法对航迹数据进行拟合,从而计算出目标的姿态角。经大量实测数据的验证表明,该方法不易受野值的影响,鲁棒性好,能满足高精度、实时估计舰船目标姿态角的要求。