Adaptive backstepping repetitive learning control design for nonlinear discrete‐time systems with periodic uncertainties

This paper addresses a tracking problem for uncertain nonlinear discrete‐time systems in which the uncertainties, including parametric uncertainty and external disturbance, are periodic with known periodicity. Repetitive learning control (RLC) is an effective tool to deal with periodic unknown components. By using the backstepping procedures, an adaptive RLC law with periodic parameter estimation is designed. The overparameterization problem is overcome by postponing the parameter estimation to the last backstepping step, which could not be easily solved in robust adaptive control. It is shown that the proposed adaptive RLC law without overparameterization can guarantee the perfect tracking and boundedness of the states of the whole closed‐loop systems in presence of periodic uncertainties. In addition, the effectiveness of the developed controller is demonstrated by an implementation example on a single‐link flexible‐joint robot. Copyright © 2014 John Wiley & Sons, Ltd.     

Two-step pyrolytic engineering to form porous nitrogen-rich carbons with a 3D network structure for Zn-air battery oxygen reduction electrocatalysis

It is of great urgency to design inexpensive and high-performance oxygen reduction reaction (ORR) electrocatalysts derived from biowastes as substitutes for Pt-based materials in electrochemical energy-conversion devices. Here we propose a strategy to synthesize three-dimensional (3D) porous nitrogen-doped network carbons to catalyze the ORR from two-step pyrolysis engineering of biowaste scale combined with the use of a ZnCl₂ activator and a FeCl₂ promotor. Electrochemical tests show that the synthesized network carbons have exhibited comparable ORR catalytic activity with a half-wave potential (~0.85 V vs. RHE) and outstanding cyclical stability in comparison to the Pt/C catalyst. Beyond that, a high electron transfer number (~3.8) and a low peroxide yield (<7.6%) can be obtained, indicating a four-electron reaction pathway. The maximum power density is ~68 mW cm^?2, but continuous discharge curves (at a constant potential of ~1.30 V) for 12 h are not obviously declined in Zn-air battery tests using synthesized network carbons as the cathodic catalyst. The formation of 3D porous structures with high BET surface area can effectively expose the surface catalytic sites and promote mass transportation to boost the ORR activity. This work may open a new idea to prepare porous carbon-based catalysts for some important reactions in new energy devices.     

餐饮废油生物柴油低温流动性的改进研究

使用气-质联用仪测定餐饮废油生物柴油(WCME)和-10号柴油(-10PD)的组成,使用冷滤点试验器和运动黏度试验器测定WCME的低温流动性,同时使用调合、添加低温流动性改进剂的方法改进WCME的低温流动性。实验结果表明,WCME主要由饱和脂肪酸甲酯和不饱和脂肪酸甲酯组成,质量分数分别为27.63%和71.81%;WCME冷滤点为0℃,运动黏度(40℃)为4.41mm2/s;WCME与-10PD调合后,冷滤点降低,其中B20的冷滤点最低,为-13℃,运动黏度随着WCME的体积分数的减少,逐渐接近-10PD的运动黏度。通过添加低温流动性改进剂,WCME,B10,B20的冷滤点分别从0,-8,-13℃降至-4,-26,-25℃。     

应急避难场所广播设计实现

应急避难场所广播体系由应急广播、场所广播室、接收端、网络接收、广播管理群、监测系统等6部分组成.针对电台在市区建立应急避难场所广播作出设计,在学校、社区、广场上安装广播系统,做到市区全方面覆盖.     

Improvement of dielectric breakdown strength and energy storage performance in Er2O3–modified 0.95Sr0.7Ba0.3Nb2O6-0.05CaTiO3 lead-free ceramics

In this study, 0.95?Sr_0.7Ba_0.3Nb₂O₆-0.05CaTiO₃-x wt% Er₂O₃ ceramics (SBNCTEx; x?=?0–5) were synthesized using traditional solid-state method, and we investigated the microstructure, energy storage properties as well as the relationship between dielectric breakdown strength and interfacial polarization. As compared with pure 0.95?Sr_0.7Ba_0.3Nb₂O₆-0.05CaTiO₃ ceramics, the Er₂O₃ dopants suppressed the grain growth of SBNCTEx, and the doped ones showed the dense microstructure. The secondary phase was found for x?≥?1 according to the EDS results, and the influence of the secondary phase on relative dielectric breakdown strength has also been studied. The dielectric breakdown strength increased from 18.1?kV/mm to 34.4?kV/mm, which is good for energy storage. The energy storage density of 0.28?J/cm³ and the energy storage efficiency of 91.4% were obtained in the SBNCTE5 ceramics. The results indicate that SBNCTE ceramics can be used as energy storage capacitors.     

移动边缘计算环境下的动态资源分配策略

在通讯设备爆炸式增长的时代,移动边缘计算作为5G通讯技术的核心技术之一,对其进行合理的资源分配显得尤为重要。移动边缘计算的思想是把云计算中心下沉到基站部署(边缘云),使云计算中心更加靠近用户,以快速解决计算资源分配问题。但是,相对于大型的云计算中心,边缘云的计算资源有限,传统的虚拟机分配方式不足以灵活应对边缘云的计算资源分配问题。为解决此问题,提出一种根据用户综合需求变化的动态计算资源和频谱分配算法(DRFAA),采用"分治"策略,并将资源模拟成"流体"资源进行分配,以寻求较大的吞吐量和较低的传输时延。实验仿真结果显示,动态计算资源和频谱分配算法可以有效地降低用户与边缘云之间的传输时延,也可以提高边缘云的吞吐量。     

Accelerated multi-contrast high isotropic resolution 3D intracranial vessel wall MRI using a tailored k-space undersampling and partially parallel reconstruction strategy

Objective

To develop a 3D multi-contrast IVW protocol with 0.5-mm isotropic resolution and a scan time of 5 min per sequence.

Materials and methods

Pre-contrast T1w VISTA, DANTE prepared PDw VISTA, SNAP, and post-contrast T1w VISTA were accelerated using cartesian undersampling with target ordering method (CUSTOM) and self-supporting tailored k-space estimation for parallel imaging reconstruction (STEP). CUSTOM + STEP IVW was compared to full-sample IVW, SENSE-accelerated IVW, and CUSTOM + zero-filled Fourier reconstruction in normal volunteers and subjects with intracranial atherosclerotic disease (ICAD). Image quality, vessel delineation, CSF suppression, and blood suppression were compared.

Results

CUSTOM + STEP vessel wall delineation was comparable to full-sample IVW and better than SENSE IVW for vessel wall delineation on T1w VISTA and luminal contrast on SNAP. Average image quality and wall depiction were significantly improved using STEP reconstruction compared with zero-filled Fourier reconstruction, with no significant difference in CSF or blood suppression.

Conclusions

CUSTOM + STEP allowed multi-contrast 3D 0.5-mm isotropic IVW within 30 min. Although some quantitative and qualitative scores for CUSTOM − STEP were lower than fully sampled IVW, CUSTOM + STEP provided comparable vessel wall delineation as full-sample IVW and was superior to SENSE. CUSTOM + STEP IVW was well tolerated by patients and showed good delineation of ICAD plaque.

     

基于时频域的卷积神经网络运动想象脑电信号识别方法

针对目前运动想象脑电（EEG）信号识别率较低的问题，考虑到脑电信号蕴含着丰富的时频信息，提出一种基于时频域的卷积神经网络（CNN）运动想象脑电信号识别方法。首先，利用短时傅里叶变换（STFT）对脑电信号的相关频带进行预处理，并将多个电极的时频图组合构造出一种二维时频图；然后，针对二维时频图的时频特性，通过一维卷积的方法设计了一种新颖的CNN结构；最后，通过支持向量机（SVM）对CNN提取的特征进行分类。基于BCI数据集的实验结果表明，所提方法的平均识别率为86.5%，优于其他传统运动想象脑电信号识别方法；同时将该方法应用在智能轮椅上，验证了其有效性。