基于内外码的产品信息分类管理系统的开发与应用

根据现代企业对产品信息分类管理的需求,研究开发了一种简洁实用的基于内外码的产品信息分类管理系统,重点介绍了编码模块和分类模块的开发方法及其功能,并应用于某公司PDM的实施工作中,促进了企业信息化进展。     

模型驱动的装备保障优化决策支持系统

以数据、模型、用户界面等要素为基础,提出了以优化模型为驱动的装备保障优化决策支持系统设计思路,拓展设计了系统总体功能结构.构建了包含算法库、模型库和应用库的模型库,引入了脚本模型,以顺序、选择或循环结构程序组合优化模型,实现复杂装备保障决策问题的求解和决策.实例应用表明系统极大地提高了部队装备精确保障能力.     

微机控制低频振动攻丝机床的研制

在金属切削加工中，螺孔的加工远比钻孔、铰孔和镗孔等孔加工复杂。目前常用研磨法来达到，造成加工效率低。为此寻找一种高效率的精密内螺纹的加工方法具有很重要的意义。本论文应用振动分析理论和频谱分析理论，确定最佳工艺参数，使机床在加工螺纹具有加工效率高、质量好的特点。     

New Delay-Dependent Stability Results for Neural Networks With Time-Varying Delay

This paper studies the problem of stability analysis for neural networks (NNs) with a time-varying delay. Unlike the previous works, the activation functions are assumed to be neither monotonic, nor differentiable, nor bounded. By defining a more general type of Lyapunov functionals, some new less conservative delay-dependent stability criteria are established in terms of linear matrix inequalities (LMIs). Meanwhile, the computational complexity of the newly obtained stability conditions is reduced because less variables are involved. Numerical examples are given to illustrate the effectiveness and the benefits of the proposed method.     

多目标支持向量机及其在少样本故障诊断中的应用

支持向量机理论简单, 实用性很强, 被大量应用于故障诊断问题中. 在分析支持向量机参数对分类结果影响的过程发现, 不恰当的参数选择往往带来较差的分类结果. 采用启发式优化方法可以避免人为选择的不足, 但单纯以等效间隔距离为寻优目标又会较大概率出现“过学习”现象. 为降低整体结构风险, 将等效间隔距离、支持向量数量和错分率等同时作为优化目标, 提出了一种基于粒子群的多目标支持向量机方法, 并采用定时重启、动态学习因子等策略提升算法全局寻优能力. 最后将其应用于多故障强关联耦合的复杂柴油机故障诊断问题中. 实验结果表明, 该方法可以有效解决少样本、不完备或不确定征兆的柴油机异响故障诊断问题, 筛选得到的综合最优解更符合人们的期望.     

LMI stability criterion with less variables for time-delay systems

Slack variables approach is an important technique for tackling the delay-dependent stability problem for systems with time-varying delay. In this paper, a new delay-dependent stability criterion is presented without introducing any slack variable. The technique is based on a simply integral inequality. The result is shown to be equivalent to some existing ones but includes the least number of variables. Thus, redundant selection and computation can be avoided so that the computational burden can be largely reduced. Numerical examples are given to illustrate the effectiveness of the proposed stability conditions. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. The authors would like to thank the Associate Editor and the Reviewers for their very helpful comments and suggestions. This work was supported in part by the Funds for Creative Research Groups of China under Grant 60821063, by the State Key Program of National Natural Science of China under Grant 60534010, by the Funds of National Science of China under Grant 60674021, 60774013, 60774047, National 973 Program of China under Grant No. 2009CB320604, and by the Funds of Ph.D. program of MOE, China under Grant 20060145019 and the 111 Project B08015. Xun-Lin Zhu received the B.S. degree in Applied Mathematics from Information Engineering Institute, Zhengzhou, China, in 1986, the M.S. degree in basic mathematics from Zhengzhou University, Zhengzhou, China, in 1989, and the Ph.D. degree in Control Theory and Engineer-ing from Northeastern University, Shenyang, China, in 2008. Currently, he is an Associate Professor at Zhengzhou University of Light Industry, Zhengzhou, China. His research interests include neural networks and networked control systems. Guang-Hong Yang received the B.S. and M.S. degrees in Northeast University of Technology, China, in 1983 and 1986, respectively, and the Ph.D. degree in Control Engineering from Northeastern University, China (formerly, Northeast University of Technology), in 1994. He was a Lecturer/Associate Professor with Northeastern University from 1986 to 1995. He joined the Nanyang Technological University in 1996 as a Postdoctoral Fellow. From 2001 to 2005, he was a Research Scientist/Senior Research Scientist with the National University of Singapore. He is currently a Professor at the College of Information Science and Engineering, Northeastern University. His current research interests include fault-tolerant control, fault detection and isolation, non-fragile control systems design, and robust control. Dr. Yang is an Associate Editor for the International Journal of Control, Automation, and Systems (IJCAS), and an Associate Editor of the Conference Editorial Board of the IEEE Control Systems Society. Tao Li was born in 1979. He is now pursuing a Ph.D. degree in Research Institute of Automation Southeast University, China. His current research interests include time-delay systems, neural networks, robust control, fault detection and diagnosis. Chong Lin received the B.Sci and M.Sci in Applied Mathematics from the Northeastern University, China, in 1989 and 1992, respectively, and the Ph.D in Electrical and Electronic Engineering from the Nanyang Technological University, Singapore, in 1999. He was a Research Associate with the University of Hong Kong in 1999. From 2000 to 2006, he was a Research Fellow with the National University of Singapore. He is currently a Profesor with the Institute of Complexity Science, Qingdao University, China. His current research interests are mainly in the area of systems analysis and control. Lei Guo was born in 1966. He received the Ph.D. degree in Control Engineering from Southeast University (SEU), PR China, in 1997. From 1999 to 2004, he has worked at Hong Kong University, IRCCyN (France), Glasgow University, Loughborough University and UMIST, UK. Now he is a Professor in School of Instrument Science and Opto-Electronics Engineering, Beihang University. He also holds a Visiting Professor position in the University of Manchester, UK and an invitation fellowship in Okayama University, Japan. His research interests include robust control, stochastic systems, fault detection, filter design, and nonlinear control with their applications.     

New delay-dependent stability results for discrete-time recurrent neural networks with time-varying delay

This paper studies the problem of stability analysis for discrete-time recurrent neural networks (DRNNs) with time-varying delays. By using the discrete Jensen inequality and the sector bound conditions, a new less conservative delay-dependent stability criterion is established in terms of linear matrix inequalities (LMIs) under a weak assumption on the activation functions. By using a delay decomposition method, a further improved stability criterion is also derived. It is shown that the newly obtained results are less conservative than the existing ones. Meanwhile, the computational complexity of the newly obtained stability conditions is reduced since less variables are involved. A numerical example is given to illustrate the effectiveness and the benefits of the proposed method.     

时滞项可微系统的时滞依赖的稳定性条件

本文研究了带有可微时滞项连续系统的稳定性问题. 通过利用时滞项导数的信息, 给出了改进的时滞系统渐近稳定性条件. 与已有的做法不同, 即便是时滞项导数的上界大于等于 1 时这个上界仍可被利用. 文中证明了所得结果比已有结果的保守性小. 同时, 由于涉及较少的决策变量, 计算复杂度也大为降低. 数例进一步说明了所得结果的有效性和少保守性.     

奇异时滞系统的时滞依赖稳定性判据

讨论了奇异时滞系统的稳定性问题. 首先, 在几个最新的结果之间建立了等价性, 并给出了一个简化的稳定性判据. 然后, 通过使用时滞分解的方法, 得到了一个新的稳定性判据. 它比现有结果具有更少的保守性. 最后, 给出了一个数值例子, 表明了新判据是有效的且保守性较小.