Adaptive Synchronization in Small-World Dynamical Networks

Adaptive synchronization in NW small-world dynamical networks was studied.Firstly,an adaptive synchronization method is presented and explained.Then,it is applied to two different classes of dynamical networks,one is a class-B network,small-world connected R o¨ssler oscillators,the other is a class-A network,small-world connected Chua's circuits.The simulation verifies the validity of the presented method.It also shows that the adaptive synchronization method is robust to the variations of the node systems parameters.So the presented method can be used in networks whose node systems have unknown or time-varying parameters.     

改进的自适应遗传算法及其在作业车间调度中的应用

针对自适应遗传算法在复杂问题应用中前期收敛速度缓慢和容易陷入局部最优的不足，引入了一种新的调节交叉概率和变异概率的方法，并提出了一种新的交叉方式，该算法很好地增强了自适应遗传算法的全局搜索能力，提高了收敛速度．通过比较几个优化实例，验证了本文算法的有效性．     

基于自适应正交变换线性组合器的EP信号压缩方法

研究了自适应正交变换线性组合器（ＡＯＴＬＣ）的原理，并将其应用于ＥＰ信号的数据压缩之中，分析和计算机模拟的结果表明，在保持同样压缩率的情况下，对ＡＯＴＬＣ压缩数据所恢复的ＥＰ信号进行潜伏期变化估计的性能，优于采用常规的差分脉冲编码调掉（ＤＰＣＭ）方法压缩重建ＥＰ信号并估计潜期变化的性能在保持各自潜伏期估计性能相近的情况下，ＡＯＴＬＣ的压缩率优于ＤＰＣＭ，另一方面，ＡＯＴＬＣ具有削弱随机噪声的能力，     

基于神经网络方法的柴油机气缸压力识别

分析了柴油机气缸盖系统激励和响应信号的非线性特性,阐述了基于BP神经网络的柴油机气缸压力识别方法.对测试的振动响应信号进行时域统计平均和低通滤波后,训练BP神经网络,利用自适应梯度下降算法,自适应调节学习速率,提高网络精度,识别柴油机气缸压力.结果表明,恢复出来的缸内压力信号和实测信号十分接近,该方法对柴油机的实时在线控制、监测和故障诊断有重要的应用价值.     

基于神经网络数字化自适应PID控制

介绍了PID调节器的数字化推导过程和采样周期的选择，讨论了一种基于神经网络的自适应PID调节器的设计。     

神经网络在车辆半主动控制中的应用

针对车辆半主动悬挂模型的非线性特性，研究了采用神经网络的自适应控制在车辆悬挂半主动控制中的应用，设计了采用前馈神经网络的辩识器和控制器，对控制器网络采用的学习规则进行了分析。仿真计算表明，采用神经网络自适应控制方法能有效改善车辆的平稳性，采用的神经网络辩识器和控制器的改进BP算法是有效的。     

基于ASA算法的大型小水线面双体船结构优化

由于小水线面双体船的结构与受力特点比普通单体船更为复杂,因此在结构的优化设计中存在更多的难点。针对小水线面双体船在横向弯曲工况下,存在着大量高应力区域的问题,本文采用自适应模拟退火算法进行优化,获得更合理的设计参数。结果表明,模拟退火算法在双体船结构的设计与优化中有着良好的工程适用性。本研究可为双体船的结构设计与优化提供参考。     

Connected variable speed limits control and car-following control with vehicle-infrastructure communication to resolve stop-and-go waves

The vision of intelligent vehicles traveling in road networks has prompted numerous concepts to control future traffic flow, one of which is the in-vehicle actuation of traffic control commands. The key of this concept is using intelligent vehicles as actuators for traffic control systems. Under this concept, we design and test a control system that connects a traffic controller with in-vehicle controllers via vehicle-to-infrastructure communication. The link-level traffic controller regulates traffic speeds through variable speed limits (VSL) gantries to resolve stop-and-go waves, while intelligent vehicles control accelerations through vehicle propulsion and brake systems to optimize their local situations. It is assumed that each intelligent vehicle receives VSL commands from the traffic controller and uses them as variable parameters for the local vehicle controller. Feasibility and effectiveness of the connected control paradigm are tested with simulation on a two-lane freeway stretch with intelligent vehicles randomly distributed among human-driven vehicles. Simulation shows that the connected VSL and vehicle control system improves traffic efficiency and sustainability; that is, total time spent in the network and average fuel consumption rate are reduced compared to (uncontrolled and controlled) scenarios with 100% human drivers and to uncontrolled scenarios with the same intelligent vehicle penetration rates.     

牵引网馈线自适应保护原理及配置方案研究

首先讨论了影响牵引网馈线保护原理及配置的因素,然后分析了牵引网馈线自适应保护的原理,其中重点探讨对距离保护传统阻抗多边形进行改进的可行性,并利用现场运行数据进行了仿真验证,最后提出了牵引网馈线自适应保护的配置方案．     

基于自适应算法的单矢量传感器抗相干干扰

将矢量传感器组合指向性vs的零点对准已知的相干干扰方向,获得"干净"的目标信号,然后结合自适应算法抵消矢量传感器原始数据中各通道的相干干扰,达到抗相干干扰的目的.文中阐述了方法的原理,进行了多种情况下的仿真,并给出实验结果.仿真和实验结果表明该方法能有效抑制方位已知的相干干扰.