基于仿人足球机器人协作定位技术研究

本文综述多机器人协作定位的研究现状,分析比较当前该领域的主要研究方向,介绍实现机器人协作定位的主要研究方法和关键技术,并总结多机器人协作定位面临的挑战和发展趋势.     

改进BP网络在航材需求预测中的应用

针对航材备件需求预测问题,在对影响航材备件需求量的多个因素进行分析研究的基础上,运用改进BP神经网络算法进行预测的仿真实验。实验结果表明,改进BP神经网络能够对积累的历史数据进行充分的应用,并且有较高的预测准确性。     

Differential Evolution Algorithm Based Self-adaptive Control Strategy for Fed-batch Cultivation of Yeast

In the fed-batch cultivation of Saccharomyces cerevisiae, excessive glucose addition leads to increased ethanol accumulation, which will reduce the efficiency of glucose utilization and inhibit product synthesis. Insufficient glucose addition limits cell growth. To properly regulate glucose feed, a different evolution algorithm based on self-adaptive control strategy was proposed, consisting of three modules (PID, system identification and parameter optimization). Performance of the proposed and conventional PID controllers was validated and compared in simulated and experimental cultivations. In the simulation, cultivation with the self-adaptive control strategy had a more stable glucose feed rate and concentration, more stable ethanol concentration around the set-point (1.0 g•L^-1), and final biomass concentration of 34.5 g-DCW•L^-1, 29.2% higher than that with a conventional PID control strategy. In the experiment, the cultivation with the self-adaptive control strategy also had more stable glucose and ethanol concentrations, as well as a final biomass concentration that was 37.4% higher than that using the conventional strategy.     

基于ENC424J600的以太网与串行接口转换技术

论述了在STM32系列的MCU上移植TCP/IP协议栈LwIP,并利用新型以太网控制器ENC424J600实现网络数据传输功能。该系统主要完成的功能是接收上位机发送的数据,并将这些数据转换成通用串行接口输出。ENC424J600是Microchip新推出的一款以太网控制器,其速度优于ENC28J60,同时为用户提供两种接口模式。本文介绍了其基于SPI接口模式下的实现过程,详细描述了该网卡驱动的硬件电路和软件流程。     

A fuzzy cerebellar model articulation controller based visual servo system for robot

This paper presents a novel online learning visual servo controller integrating the FCMAC with proportion controller for the control of position of manipulator end-effector. Since the FCMAC has good learning capability and fast learning speed, and can save much computer memory space by fuzzy processing of input space division and memory unit activation, it is used to develop an adaptive control law by learning the relationship between the image feature errors and manipulator input, and the aim of online learning of the FCMAC is to minimize the output of proportion controller. Furthermore, the FCMAC has no need for models of robot manipulator and image feature extraction, so that the capability of proposed controller for tasks under uncertain environment can be improved. Finally, the proposed controller is proved to be effective by the experiment, and compared with BP neural network.     

Improved stability conditions for systems with interval time-varying delay

The paper is concerned with the stability of linear systems with interval time-varying delay. Through constructing a new augmented Lyapunov-Krasovskii functional (LKF) which contains some quadruple-integral terms and estimating the time derivative of the LKF less conservatively, new stability criteria are derived without introducing any free matrices. Moreover, by proving the positive definiteness of the LKF with some integral inequalities, the constraints on some functional parameters are relaxed and the conservatism of the obtained results are further reduced. Numerical examples are also given to demonstrate the effectiveness and reduced conservatism of the obtained results.     

基于内容的静态语义概念视频检索方法研究

本文针对互联网视频检索技术的发展,阐述了目前主流视频搜索引擎的技术现状,分析了互联网视频检索的关键技术,特别是对于视频特征的提取技术。本文的创新点是提出了一种通用的基于内容的静态语义视频检索方法,该方法可以弥补基于文本视频检索的有关不足,并且在TRECVID的视频概念检索数据的静态语义概念中得到验证,运行稳定。     

基于CaO引导的甲烷蒸汽重整化学链燃烧制氢系统

为在重整气中得到高纯H_2和降低尾气CO_2分离成本,建立了基于CaO引导的甲烷蒸汽重整化学链燃烧制氢系统,该系统在重整反应器中加入CaO吸收剂,用以吸收重整器内的CO_2,提高重整气中H_2浓度,形成的CaCO_3固体在煅烧器中受热分解重新生成CaO。利用Aspen Plus进行了过程模拟及热力学分析,并研究主要参数对系统性能的影响,得到优化的操作条件为:CaO循环量/CH_4比为0.5,CH_4(燃料)/CH_4比为0.35,NiO循环量/CH_4比为1.4。CaO循环量/CH_4比从0变化到0.5时,重整气中H_2浓度从0.60增长到0.99;CH_4(燃料)/CH_4比在0.25~0.45区间变化时,重整气中H_2浓度从0.86提高到0.99,产气量增加;NiO循环量/CH_4比在1~1.6区间变化时,重整气中H_2浓度从0.88增长到0.99,系统有效能效率变化较小。     

Discriminative multi-task objects tracking with active feature selection and drift correction

In this paper, we propose a discriminative multi-task objects tracking method with active feature selection and drift correction. The developed method formulates object tracking in a particle filter framework as multi-Task discriminative tracking. As opposed to generative methods that handle particles separately, the proposed method learns the representation of all the particles jointly and the corresponding coefficients are similar. The tracking algorithm starts from the active feature selection scheme, which adaptively chooses suitable number of discriminative features from the tracked target and background in the dynamic environment. Based on the selected feature space, the discriminative dictionary is constructed and updated dynamically. Only a few of them are used to represent all the particles at each frame. In other words, all the particles share the same dictionary templates and their representations are obtained jointly by discriminative multi-task learning. The particle that has the highest similarity with the dictionary templates is selected as the next tracked target state. This jointly sparsity and discriminative learning can exploit the relationship between particles and improve tracking performance. To alleviate the visual drift problem encountered in object tracking, a two-stage particle filtering algorithm is proposed to complete drift correction and exploit both the ground truth information of the first frame and observations obtained online from the current frame. Experimental evaluations on challenging sequences demonstrate the effectiveness, accuracy and robustness of the proposed tracker in comparison with state-of-the-art algorithms.     

联合 LTP 和 LPQ 的人脸识别方法

提出一种联合局部三值模式（LTP）和局部相位量化（LPQ）的人脸识别方法,该方法首先对预处理后的人脸分别采用LTP算子、LPQ算子提取各自的直方图,然后,通过特征选择将两者联合为LTP＿LPQ直方图,最后通过最近邻分类器进行分类识别。在ORL和YALE标准人脸数据库上的实验表明,该方法能有效地提高人脸的识别率。