柴油机双层隔振系统耦合振动主动控制仿真研究

本文针对双层隔振系统多自由度耦合振动的特性,设计了以ⅡR滤波器为基本组成单元的多输入多输出（MIMO）自适应控制器,推导出相应的自适应算法－多误差x-RLMS算法,并进行了双层隔振系统耦合振动主动控制的仿真研究,结果表明,控制算法有较好的收敛性与稳定性,取得了较好的控制效果。     

An Improvement of Russo's Fuzzy Noise-Filtering for Image Processing

We adapted Russo's image noise filtering technique by introducing an adaptive parameter, noise possibility. This parameter potentially indicates whether a pixel is noise. The improved Russo's method was applied to process the Lena image and a remote sensing image corrupted by noise. The results show that it has a stronger noise filtering ability than other traditional techniques such as Wiener filtering.     

基于神经网络方法的车内噪声自适应主动控制

建立了一种基于神经网络方法的车内噪声主动控制系统。用Elman神经网络对驾驶员耳旁噪声信号进行识别、预测，并用LSLL自适应信号处理方法对车内低频噪声进行主动控制。通过在稳态工况下对被测试轻型客车的试验研究表明，此系统能有效降低车内低频噪声。     

自适应小波网络在船舶噪声识别中的应用

本文基于自适应小波网络理论,构造了一个应用于船舶辐射噪声识别的自适应小波网络分类器。仿真结果表明,该方法具有良好的目标识别性能,且收敛速度快,是一种有效的目标识别方法,从而为研究自适应小波网络理论在声呐信号目标识别领域中的应用有着极其重要的实际意义。     

基于驾驶员行为模拟的ACC控制算法

基于驾驶员最优预瞄加速度模型建立了一种适用于多种典型行驶工况的ACC控制算法。该算法采用基于多目标模糊决策方法的驾驶安全性、工效性、轻便性与合法性评价指标以及基于预瞄跟随理论的微分校正函数，描述了ACC控制系统对自由工况、跟随工况和切入工况等不同行驶条件及汽车动力学系统强非线性特性的考虑。     

基于VDM与APSO优化极限学习机的船舶运动姿态预报

为提高船舶在海上运动的耐波性与适航性,并为解决具有非线性、随机性和非平稳性特点的船舶运动姿态难以准确预测的问题,提出运用一种基于变分模态分解和自适应粒子群算法优化极限学习机的组合预测模型。该算法首先利用变分模态分解将船舶运动姿态序列分解为一系列限带内本征模态函数,并且变分模态分解可以避免经验模态分解技术所产生的模态混叠和端点效应,可以降低序列的非平稳性对预测精度的影响;然后对各模态分量分别建立极限学习机预测模型,并用改进的粒子群算法对极限学习机的初始权值和阈值进行优化;最后将各模态分量预测结果进行叠加,得到最终的船舶运动姿态预测值。通过模拟试验测试并与其他传统的预测方法进行比较,结果表明所建立的组合预测模型具有更高的预测精度。     

Lateral Vehicle Behaviour: Comparison of Subjective/Objective Assessment Using the Choquet Integral

This paper presents an original method for the aggregation of transverse behaviour indicators obtained first from a subjective assessment then from an objective one of different vehicles tested under normal working conditions. The Choquet integral is used with respect to fuzzy measures. The main advantage of this method is to take account of the existing interactions between the indicators: redundancy, complementarity, inde-pendence. When this tool is used for subjective and objective evaluations, the computation methods of the objective indicators can be validated. Moreover, the influence of the human factor in the judgment of vehicle behaviour is easier to understand.     

A two-stage fuzzy logic controller for traffic signals

This paper presents the design and evaluation of a fuzzy logic traffic signal controller for an isolated intersection. The controller is designed to be responsive to real-time traffic demands. The fuzzy controller uses vehicle loop detectors, placed upstream of the intersection on each approach, to measure approach flows and estimate queues. These data are used to decide, at regular time intervals, whether to extend or terminate the current signal phase. These decisions are made using a two-stage fuzzy logic procedure. In the first stage, observed approach traffic flows are used to estimate relative traffic intensities in the competing approaches. These traffic intensities are then used in the second stage to determine whether the current signal phase should be extended or terminated. The performance of this controller is compared to that of a traffic-actuated controller for different traffic conditions on a simulated four-approach intersection.     

含齿隙环节伺服系统的反步积分补偿控制

齿隙的存在成为影响机电伺服系统动态性能和稳定性的一个重要因素。为了减小其不利影响,提出了反步积分自适应齿隙补偿方法。本文依据Lyapunov稳定性理论,应用反步积分方法,逐步递推选择Lyapunov函数,设计了基于状态反馈的自适应控制器。通过理论分析以及与传统PID控制的仿真结果比较表明,该方法显著地降低了齿隙对伺服性能的影响,从而提高了系统的跟踪精度和鲁棒性。     

基于同心圆分簇的无线传感器网络路由协议的研究

针对无线传感器网络中LEACH协议的簇头分布不均匀以及不适合远距离传输数据的缺点,提出一种基于同心圆的分簇路由协议(CBCR).CBCR不仅改进选簇方法,而且引入管理节点负责簇头的选举.给出该协议的实现过程,通过与LEACH的比较,证明该协议能有效延长网络存活时间.