Adaptive Neural Network Finite-Time Control for Uncertain Robotic Manipulators

An adaptive neural network finite-time controller (NNFTC) for a class of uncertain nonlinear systems is proposed by using the backstepping method, which employs an adaptive neural network (NN) system to approximate the structure uncertainties and uses a variable structure term to compensate the approximation errors, thus improving the robustness of the system to external disturbances. The controller is then applied to uncertain robotic manipulators, with a control objective of driving the system state to the original equilibrium point. It is proved that the closed-loop system is finite-time stable. Moreover, simulated and experimental results indicate that the proposed NNFTC is effective and robust.     

微液滴现象与大气腐蚀——Ⅱ.微液滴现象的电化学表征

用扫描Kelyin探头和电化学极化等手段,研究了微液滴现象与大气腐蚀的电化学过程之间的相关性.扫描Kelvin探头测定主液滴周围的电位分布显示,微液滴只在表面的正电性区域出现;当有微液滴形成时,火山形电位分布的峰高且宽、谷深且窄;同时,峰变宽的速率与微液滴的扩展速率近似相等.电化学极化结果显示,微液滴的成核速率随极化电流的增加而线性加速,促使大气腐蚀过程发生的电位差和相应的腐蚀电流是微液滴形成和发展的推动力.     

冷辗扩机圆度辊随动约束力与随动位置分析

为保证环件圆度、提高环件精度,必须对冷辗扩机圆度辊进行力和位置的实时控制与调节,这是冷辗扩工艺控制中的一个难点。根据冷辗扩原理,分析了冷辗扩过程中圆度辊的随动约束力和随动位置与轧制力及环件瞬时外圆半径的关系,得到了一个数学模型,为圆度辊机构的设计和控制提供了理论依据。     

Group decision making with multi-attribute interval data

The aim of this paper is to present a group decision making methodology, in which the decision information, including the attribute values, attribute weights and weights of decision makers, is expressed in interval data. An extended TOPSIS technique is twice used in the proposed method, which is first used to determine the weights of decision makers, and second used to rank the preference order of alternatives. There is no aggregation of decision information in decision process, except that the ideal decisions as auxiliary decision tools are used in decision process. We give a comparison with another method for group decision making to show the technical advance of reported method. Additionally, we also give a real life application for supplier selection and a discussion to test the effectiveness and practical implications of the proposed method.     

超疏水FeNi2O4/甲基丙烯酸乙烯酯-二乙烯苯共聚物多孔材料的制备及其油水分离应用

为了应对日益频发的溢油事故,实现含油水体的净化,通过高内相Pickering乳液模板法制备了FeNi₂O₄掺杂的甲基丙烯酸乙烯酯-二乙烯苯共聚物多孔材料。采用FTIR、SEM、TGA、VSM、接触角测量仪、静态压汞仪、万能试验机等对材料结构与性能进行表征与分析。结果表明,材料具有三维分级多孔结构,孔径主要分布于3 μm及6~14 μm且大孔孔径可调节。材料热稳定性好,初始热分解温度最高达300℃。FeNi₂O₄纳米粒子的引入不仅提升了乳液稳定性,也赋予材料磁响应性。材料具有良好的疏水亲油性,水接触角达151°、滚动角为5°、油接触角为0°,吸油速率快,并具有良好的重复利用性和优异的油水吸附选择性,对多种油品及有机溶剂的饱和吸附倍率达40.80~93.08 g·g?1,且保油率均在90%以上。探究了材料的孔结构调控,发现,改变乳液的内相比可以调节材料的大孔分布、孔隙率、密度、比表面积、吸油倍率和力学性能。综上说明:超疏水FeNi₂O₄/甲基丙烯酸乙烯酯-二乙烯苯共聚物多孔材料可以高效分离水中油污,对水体环境的治理与净化具有现实意义。      

海洋食品微生物生长智能通用预测平台

针对海洋食品对虾生产加工的特点,设计与开发了对虾生产加工中微生物生长智能通用预测平台,为海洋食品的安全生产与加工提供分析手段。     

A reference-based blind source extraction algorithm

By utilizing a priori information available as reference, constrained independent component analysis (cICA) or independent component analysis with reference (ICA-R) achieves some advantages over other methods. However, ICA-R is very time-consuming; moreover, it is very difficult to determine its threshold parameter, once the value is improperly chosen the algorithm will fail to converge. In order to overcome these drawbacks, a very simple blind source extraction method, whose optimization function is simply the closeness measure between the desired output and its corresponding reference in ICA-R, is proposed in this paper. Experiments with synthesized data and real-world electrocardiograph data confirm its validity and superiority.     

基于改进伪中值滤波器的道路图像滤波算法*

针对已有的细胞神经网中值滤波器滤波时,收敛速度慢、稳定性不好以及滤波图像比较模糊的缺点,设计一种差值控制细胞神经网的改进伪中值滤波器。提出了改变取值空间、引入随机扰动、扩大中值滤波窗口尺度和引入Mask掩图的改进方法。实验结果表明：该算法具有去除各种强度脉冲随机噪声能力,又能保护图像细节信息,而且具有良好的实时性。     

一种正余弦变换的改进高效算法

在最速下降法的基础上,给出了地球物理勘探中计算一种正余弦变换的一个有效数值算法,同时对新算法产生的误差进行了理论分析,并用数值实验对理论分析进行了检验．误差的理论分析及数值实验的结果证明了该算法具有较高的精度。