可变速智能车辆车道变换控制研究

提出了一种能够兼顾横向控制和纵向控制的可变速自动换道控制方法。首先建立了可变速的车辆运动方程,并采用基于动态目标位置概念的控制机制,以模糊逻辑为控制策略,以T-S模糊模型为控制结构,以自适应神经网络为隶属度函数的参数调整手段,设计出一种兼顾智能车辆横向控制和纵向控制的运动控制器。仿真结果表明,提出的控制方法是可行的、有效的,并且较为理想地模拟实际交通环境中车辆换道的行为特性。     

水风光互补适应性调度的集合卡尔曼滤波方法北大核心CSCD

水风光互补是实现能源转型、助力碳中和的重要途径。传统的水风光互补中长期调度模型,忽略了气候变化和人类活动引起的水风光资源变异,得到的静态调度规则难以适应变化环境。为此,本研究采用集合卡尔曼滤波技术开展适应性调度研究。首先进行确定性优化调度,得到最优运行轨迹;其次识别调度函数的决策变量与自变量,构建线性调度函数;最后采用集合卡尔曼滤波动态更新调度函数的参数,形成适应性调度规则。以锦屏一级水电站及周边风、光电站为实例,研究表明适应性调度规则较常规调度和静态调度,在检验期年均发电量分别提高6.45亿k W·h和0.53亿k W·h,说明论文所提方法可有效追踪最优轨迹的变化来适应变化环境。     

图像识别的仓库装配智能车

本文介绍了基于图像采集和图像识别技术的智能装配车的基本设计原理,系统硬件组成和控制算法。在此基础上设计了可以实现自主运载、自主循迹、自主识别,且具有更高的灵活性、后期可维护性、功能可扩展性、更快的运作速度、高精度控制等优点,使得装配的效率将大大提高,并且降低错误装配造成的返工成本,该系统具有广泛的应用前景。     

Travel time models for deep-lane unit-load autonomous vehicle storage and retrieval system (AVS/RS)

Autonomous vehicle storage and retrieval systems use vehicles that move horizontally along rails within the storage racks, while vertical movements are provided by lifts. The solution proposed in this paper addresses a particular system configuration that works with multiple deep storage lanes that are widely used in the food and beverage industry, characterised by large volumes of products of limited variety. The generic deep lane is single item, i.e. one stock keeping unit, and single batch, i.e. one production lot, thereby affecting the performance of the system in terms of storage capacity utilisation and throughput. Determining the number and depth of the lanes is crucial to aid the design and control of such a storage system. The aim of this paper was to support the design of AVS/RSs though a set of original analytic models for the determination of the travelled distance and time for single-command and dual-command cycles given alternative layout configurations. The models are validated by simulation and exemplified with a real-warehousing case study. The paper presents useful guidelines for the configuration of the system layout including the determination of the optimal shape ratio and the length of the lanes.     

Multivariable linearizing control of an industrial sugar crystallization process

This paper illustrates the benefits of a multivariable linearizing control approach applied to an industrial crystallization process. This relevant approach proposes a setpoint tracking for the crystal mass/concentration couple. In this purpose, a model dedicated to last stage crystallization is designed, without consideration of crystal size distribution. The controlled variables, unavailable, are obtained using an extended Luenberger observer. The observer is validated on industrial data and shows good performance in both convergence rate and accuracy. The performance of the proposed linearizing strategy, which application to cane sugar crystallization constitutes a real novelty, is tested via simulation. The good performance in setpoint tracking, even in presence of noise, disturbances and modeling error, allows to consider a significant improvement of the global productivity.     

基于传感器的汽车主动安全设计

从汽车主动安全方面进行研究,通过对车辆道路行驶时关键要素的危险状态识别,实现完善汽车主动安全性能.本设计采取自动控制方法,通过研究汽车防碰撞检测和预防以及偏离车道报警,为汽车安全系统提供信息支持,实现车辆主动避免碰撞危险,减少或避免交通事故发生,大大提高汽车行驶主动安全性.所设计汽车主动安全防撞系统主要包括激光防撞测距、激光车道检测、报警警示系统等.     

基于激光雷达距离图像的道路边缘检测与跟踪

论述了将激光雷达的距离图像信息用于道路检测和跟踪。首先将扫描点进行聚类分析对道路边缘进行检测和对所检测的边缘进行最小二乘直线拟合,在成功检测道路边缘后,利用Kalman滤波对道路边缘进行跟踪。实验证明该算法具有检测准确且鲁棒性好的特点。     

一种新的车道线快速识别算法

针对现有的的车道线识别算法在复杂环境下识别率低、鲁棒性和实时性较差的问题,提出了一种基于形态学多结构元素建模的车道线快速识别算法。该算法首先对车道图像进行感兴趣区域提取,通过Canny算子对感兴趣区域进行边缘检测,然后利用具有车道模型特征的多结构元素进行车道线提取、霍夫变换,以及峰值检测点参数的筛选,从而得到实际车道左右标识线的参数以重建原车道线。仿真实验表明,该算法能在多种复杂环境下快速、准确地识别出车道标识线,且鲁棒性高。     

军校新生学员的转型问题探析

为使军校新生学员尽快融入军校的知识学习和军事训练之中,归纳了军校新生学员因环境变化而带来的思想、生活、自主学习、心理和人际交流等5个方面＂不适应＂的主要表现,分析了产生这些＂不适应＂表现的家庭、社会教育和新生自身3种主要原因,提出了加强思想教育和心理适应教育、确立学习奋斗目标、改进学习方法、教员注意教法上的衔接、营造和谐的学习生活环境、发挥队干部和新生干部作用等主要措施.