深海采矿双波浪补偿系统自适应跟踪控制

为满足深海采矿过程中管道的快速自动对接要求,设计了一种能够同时进行布放回收和升沉补偿的双波浪液压补偿系统.基于波波夫超稳定理论,设计了上波浪补偿的自适应跟踪控制律.仿真实验结果表明,上波浪补偿系统能够在自适应跟踪控制律作用下,迅速跟踪下波浪补偿系统的升沉运动,其跟踪精度能够满足同步对接要求.     

Design of an adaptive controller for dive-plane control of a torpedo-shaped AUV

Underwater vehicles operating in complex ocean conditions present difficulties in determining accurate dynamic models. To guarantee robustness against parameter uncertainty, an adaptive controller for dive-plane control, based on Lyapunov theory and back-stepping techniques, was proposed. In the closed-loop system, asymptotic tracking of the reference depth and pitch angle trajectories was accomplished. Simulation results were presented which show effective dive-plane control in spite of the uncertainties in the system parameters.     

基于拓扑识别的舰船电力系统自适应保护策略

舰船电力系统使命的特殊性及系统配置的独特性使其继电保护策略与陆地电力系统有所不同.随着系统容量和网络结构的不断发展,以离线整定为特征的传统三段式电流保护已不能满足保护要求.通过分析舰船电力系统保护的特点和需求,提出基于拓扑识别的自适应保护策略,能根据系统网络拓扑结构自动在线调整保护整定值.典型实例的分析结果验证了其在改善保护性能方面的可行性及有效性.     

基于AOK-TFR的轨道电路故障诊断方法

为弥补现有补偿电容检测方法在检测及时性和检测成本等方面的不足,基于传输线理论,提出了机车信号感应电压幅值包络(IVECS)仿真模型;在此基础上,分析了补偿电容故障对IVECS的影响规律,建立并验证了基于频率的IVECS等效回归模型;利用补偿电容故障位置前后IVECS的频率变化,提出了基于自适应最优核时-频分布的补偿电容故障诊断方法.该方法基于机车信号的实际数据,采用B样条离散二进小波对数据进行滤波降噪处理,并利用自适应最优核时-频分布提取处理结果的时-频信息,再通过检测时-频信息中频率的变化实现对故障电容的定位.经过对随机抽取的100段实际数据的测试,准确率约为92.58%,表明该方法能准确检测轨道电路发生故障的补偿电容位置.     

一种自适应正则化参数和模数的图像去卷积方法

自适应正则化方法是解决图像去卷积问题中平滑噪声和保持边缘矛盾的一种方法,传统的自适应正则化方法只考虑到图像的整体信息而忽略了图像内部不同区域的细节信息,本文提出的自适应正则化方法,利用Katsaggelos自适应正则化参数,自适应的改变正则化参数,并通过图像内部不同区域的信息自适应改变正则化模数矩阵．从而实现了平滑噪声和保持边缘的平衡,既保持了边缘又抑制了噪声,取得了更好的去卷积效果．     

舰船电力系统自适应保护技术研究

随着舰船电力系统的不断发展,系统配置、网络结构和运行模式等方面较传统舰船电力系统都发生了较大的改变,以离线整定为特征的三段式电流保护方法已不能满足要求.在全面分析传统继电保护特性的基础上,提出舰船电力系统自适应保护策略,利用网络结构和系统状态自动在线调节保护整定值,可以有效地提高保护的灵敏性和选择性.     

船舶汽轮机组优化设计研究

汽轮机组是船舶动力装置的重要组成部分,其重量和尺寸是影响船舶动力装置重量体积及布置的重要因素.建立包括汽轮机、冷凝器和齿轮减速器设计三部分的船舶汽轮机组数学模型,以汽轮机组重量最小为目标函数和在给定的约束条件下,采用不同的优化算法对机组进行了优化设计.与原方案相比,采用优化方案后汽轮机组重量明显减小,改进的自适应遗传算法有更好的优化性能,优化效果显著.     

Human driving data-based design of a vehicle adaptive cruise control algorithm

This paper presents a vehicle adaptive cruise control algorithm design with human factors considerations. Adaptive cruise control (ACC) systems should be acceptable to drivers. In order to be acceptable to drivers, the ACC systems need to be designed based on the analysis of human driver driving behaviour. Manual driving characteristics are investigated using real-world driving test data. The goal of the control algorithm is to achieve naturalistic behaviour of the controlled vehicle that would feel natural to the human driver in normal driving situations and to achieve safe vehicle behaviour in severe braking situations in which large decelerations are necessary. A non-dimensional warning index and inverse time-to-collision are used to evaluate driving situations. A confusion matrix method based on natural driving data sets was used to tune control parameters in the proposed ACC system. Using a simulation and a validated vehicle simulator, vehicle following characteristics of the controlled vehicle are compared with real-world manual driving radar sensor data. It is shown that the proposed control strategy can provide with natural following performance similar to human manual driving in both high speed driving and low speed stop-and-go situations and can prevent the vehicle-to-vehicle distance from dropping to an unsafe level in a variety of driving conditions.