High-speed train control based on multiple-model adaptive control with second-level adaptation

Speed uplift has become the leading trend for the development of current railway traffic. Ideally, under the high-speed transportation infrastructure, trains run at specified positions with designated speeds at appointed times. In view of the faster adaptation ability of multiple-model adaptive control with second-level adaptation (MMAC-SLA), we propose one type of MMAC-SLA for a class of nonlinear systems such as cascaded vehicles. By using an input decomposition technique, the corresponding stability proof is solved for the proposed MMAC-SLA, which synthesises the control signals from the weighted multiple models. The control strategy is utilised to challenge the position and speed tracking of high-speed trains with uncertain parameters. The simulation results demonstrate that the proposed MMAC-SLA can achieve small tracking errors with moderate in-train forces incurred under the control of flattening input signals with practical enforceability. This study also provides a new idea for the control of in-train forces by tracking the positions and speeds of cars while considering power constraints.     

模糊自适应滤波在车载组合导航系统中的应用

文章针对车载GPS/DR组合导航系统工作环境复杂,其观测噪声相应复杂多变的特点,引入了一种基于模糊自适应控制的卡尔曼滤波算法。这一方法基于方差匹配的思想,通过模糊控制器在线调整观测噪声方差,以改变滤波器的自适应性,从而提高导航精度。文章最后对GPS/DR系统进行了仿真,结果表明采用此方法后的滤波精度优于常规Kal-man滤波的结果。     

一种船舶电力滤波器的仿真研究

在小型船舶电力推进系统中,变频驱动产生了严重的谐波污染,导致电力系统的容量大大增加,恶化电网电能质量,甚至影响了船舶安全运行.针对电力推进船舶电网存在的谐波污染问题,设计了电力滤波器的拓扑结构,制定其控制策略,分析该滤波器的工作原理,并进行计算机仿真,验证了该滤波器的有效性.     

基于卡尔曼滤波算法的电机转速精确估计

从无刷直流电机入手建立数学模型，利用卡尔曼Kalman（EKF）滤波原理算法，对无刷直流电机的转速进行精确估计，然后在Matlab环境下仿真，验证卡尔曼滤波算法对电机转速估计的精确性。     

舰船电力系统自适应电流保护网络拓扑分析

舰船电力系统自适应电流保护是根据电网的运行方式、网络结构和故障类型等来实时改变保护定值或保护性能，使保护最优化。网络拓扑结构的变化可以通过检测开关、断路器等的开断和闭合情况以及线路电流、电压的变化来确定，它是进行保护分析的基础。本文简单介绍了舰船电力系统保护研究的现状，阐述了引入舰船电力系统自适应电流保护的重要性，并主要论述了如何通过节支关联矩阵来对网络结构变化进行跟踪。     

Road roughness estimation based on discrete Kalman filter with unknown input

ABSTRACT

The road roughness acts as a disturbance input to the vehicle dynamics, and causes undesirable vibrations associated with the ride and handing characteristics. Furthermore, the accurate measurement of road roughness plays a key role in better understanding a vehicle dynamic behaviour and active suspension control systems. However, the direct measurement by laser profilometer or other distance sensors are not trivial due to technical and economic issues. This study proposes a new road roughness estimation method by using the discrete Kalman filter with unknown input (DKF-UI). This algorithm is built on a quarter-car model and uses the measurements of the wheel stroke (suspension deflection), and the acceleration of the sprung mass and unsprung mass. The estimation results are compared to the measurements by laser profilometer in-vehicle test.     

简化UKF算法在SINS／GPS组合导航中的应用

针对SINS／GPS组合导航系统的特点，建立了系统的非线性误差模型。根据系统状态方程为非线性而观测方程为线性的特点，将一种简化的UKF方法（Rao-Blackwellisation Additive Unscented Kalman Filter，RBAUKF）用于SINS／GPS组合导航系统中，RBAUKF采用较少的采样点数目和简化的更新算法，降低了计算复杂度。最后，在机动条件下，进行了SINS／GPS组合导航实验仿真。仿真结果表明，RBAUKF相比EKF具有更高的滤波精度，更适合在SINS／GPS组合导航系统中应用。     

防金属粉末型内燃机车空气滤清器的研制

对GK1型内燃机车的空气滤清器进行了分析,并指出其在冶金企业运用中的缺陷,研制了一种防金属粉末的磁性滤网,并在机车空气系统得到了良好应用。     

大型船舶航迹多变量随机最优控制

基于随机控制理论，研究了大型船舶航迹的随机最优控制。以Mariner号船舶为研究对象，建立了该船的运动方程和干扰模型，在此基础上，利用卡尔曼滤波器对航向角Ψ、舵角δ、船位信息(经纬度)等进行最优估计，采用LQG随机控制方法对航迹进行随机最优控制。仿真结果表明航迹控制性能良好，能精确保持航迹。     

导航信号卡尔曼滤波定位解算方法研究

研究了导航信号的卡尔曼滤波定位解算方法，该方法能够实现用小全的测量值完成导航解的估值解算，同时还可以对导航解进行平滑，减小噪声对导航解的影响。仿真结果证明了该方法在导航定位解算中的有效性和可行性。