Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

子母车系统效率分析与验证

在子母车系统中,研究一台母车配合两台子车在同层进行复合作业的效率问题,提高系统作业效率计算的准确性,优化系统整体布局和物流设备的选择。首先分析一台母车配合两台子车在同层的循环复合作业过程;然后结合子母车的运动特性得到其作业效率计算模型;最后采用MATLAB工具计算效率模型分别在随机组合作业对和FEM9.851标准作业对的作业效率,通过对比验证,两种循环作业的效率绝对偏差符合工程实际。在工程实际中可以参照FEM9.851标准作业对代替随机组合作业对进行子母车系统的效率计算。     

基于关键水平的水下采油树预防性维修决策方法

为解决电液复合水下采油树在运行过程中工作环境恶劣且复杂、系统要求可靠性高、维修难度大且费用高的问题,建立基于伽马退化过程的水下采油树组件可靠度退化模型和考虑维修花费、停产损失在内的维修成本模型,建立水下采油树系统预防性维修优化目标体系,基于多目标粒子群优化算法对维修策略进行优化。建立的模型可有效描述水下采油树系统的工作特性,最优解能够满足在低维修成本的前提下系统高可靠性的工作要求。     

Disappearance and recovery of colossal permittivity in (Nb+Mn) co-doped TiO2

We investigate the effects of doping and annealing on the dielectric properties of metal ions doped TiO₂ ceramics. Colossal permittivity (CP) above 10⁴ was observed in single Nb ion doped TiO₂, which was dominated by electron transport related interfacial polarization. Moreover, the CP can be dropped to 120 when simultaneously introducing Mn ion into the sample. The disappearance of CP behaviors maybe due to the multivalence of Mn which would inhibit the reduction of Ti⁴⁺ to Ti³⁺, and thus reduce delocalized electrons. Interestingly, the CP was recovered for the (Nb+Mn) co-doped TiO₂ after post-sintering heat treatment in N₂ atmosphere. The recovery of CP in the sample after annealing can be ascribed to the semiconducting grain and the insulating grain boundary, according to impedance spectroscopy. We therefore believe that this work can help us understand the mechanism of CP from a new perspective.     

基于特征融合的中文简历解析方法研究

针对基于规则和统计的传统中文简历解析方法效率低、成本高、泛化能力差的缺点，提出一种基于特征融合的中文简历解析方法，即级联Word2Vec生成的词向量和用BLSTM（Bidirectional Long Short-Term Memory）建模字序列生成的词向量，然后再结合BLSTM和CRF（Conditional Random Fields）对中文简历进行解析（BLSTM-CRF）。为了提高中文简历解析的效率，级联包含字序列信息的词向量和用Word2Vec生成的词向量，融合成一个新的词向量表示；再由BLSTM强大的学习能力融合词的上下文信息，输出所有可能标签序列的分值给CRF层；再由CRF引入标签之间约束关系求解最优序列。利用梯度下降算法训练神经网络，使用预先训练的词向量和Dropout优化神经网络，最终完成对中文简历的解析工作。实验结果表明，所提的特征融合方法优于传统的简历解析方法。     

提高琅琊山选矿厂铁回收率试验

琅琊山选矿厂为了提高选铁回收率，进行了粗、精、扫选磁场强度试验及磨矿细度对铁回收的影响试验。结果表明：①增大扫选磁场强度可以提高精矿铁回收率0.37个百分点；扫选磁场强度从168 kA/m提高到240 kA/m，磁性铁回收率从89.79%提高到90.86%。②磁性铁主要以微细粒流失在尾矿中，回收难度极大。③以增大扫选磁场强度可提高铁回收率0.37个百分点计算，每年可增加销售收入约14.6万元，大半年即可收回设备改造投资。     

基于图像增强的去雾快速算法的FPGA实现

基于图像增强方法，本文提出了一种使用亮度映射的图像去雾快速算法。此算法通过调整室外多雾场景图像的对比度，提高了雾中物体的辨识度。算法的复杂度低、处理延迟小，实时性高，利于FPGA的实现。实现时不需外存储器，延时为ns级，并提供了强度调节接口，以适应较广的应用环境。     

PET的紫外老化性能及机理研究

采用力学、紫外-可见光分析和热失质等测试手段研究了PET改性料的紫外老化性能及老化机理。结果表明:复合助剂的加入能显著提升体系的力学性能保持率,进而提升其紫外老化寿命,提升的幅度随复合助剂中耐紫外剂含量的增加而显著增加。DSC分析表明,随着复合助剂的引入和老化的进行,改性料结晶度增加。文中进一步讨论了PET改性料的紫外老化机理。紫外-可见光分析表明,紫外老化能产生醌类和双醌类物质,进而提升PET改性料的紫外吸收度。