Adaptive SPC monitoring scheme for DOE-based APC

Automatic process control （APC） based on design of experiment （DOE） is a cost-efficient approach for variation reduction. The process changes both in mean and variance owing to online parameter adjustment make it hard to apply traditional SPC charts in such DOE-based APC applied process. An adaptive SPC scheme is developed, which can better track the process transitions and achieve the possible SPC run cost reduction when the process is stable. The control law of SPC parameters is designed by fully utilizing the estimation properties of the process model instead of traditionally using the data collected from the production line. An example is provided to illustrate the proposed adaptive SPC design approach.     

New results on the robust stability analysis of neural networks with discrete and distributed time delays

Delay-dependent robust stability of cellular neural networks with time-varying discrete and distributed time-varying delays is considered. Based on Lyapunov stability theory and the linear matrix inequality （LMIs） technique, delay-dependent stability criteria are derived in terms of LMIs avoiding bounding certain cross terms, which often leads to conservatism. The effectiveness of the proposed stability criteria and the improvement over the existing results are illustrated in the numerical examples.     

Robust model predictive control of continuous uncertain systems*

The authors concern robust model predictive control for linear continuous systems with polytopic uncertainties and input constraints. At each sampling time, a piecewise constant control sequence is obtained by solving a set of linear matrix inequalities. The sufficient conditions on the existence of the model predictive control are given, and the robust stability of the closed-loop systems is guaranteed. A simulation example illustrates the efficiency of the proposed method.     

在多目标决策中利用基点计算权重

给出了一种利用基点计算权重的多目标决策方法 .该方法所需信息量小 ,并能获得满意的排序结果 .     

一类非线性离散系统的自适应控制

针对一类非线性离散系统 ,利用 Lyapunov方法和加权最小二乘估计设计了一种自适应控制器 ,在对非线性 (不加增长条件约束 )的情况下 ,得到了闭环系统的全局跟踪性能 .     

船舶力控减摇鳍伺服系统研究

针对船舶力控减摇鳍伺服系统,运用H∞控制理论考虑混合灵敏度S／KS问题设计了控制器,由于混合灵敏度S／KS问题模型、权函数的选择、系统奇异性对等实际问题是H∞控制理论应用于实践的关键问题,因此本文结合船舶力控减摇鲁伺服系统着重对这些问题进行了研究,这种思想对于将方法设计的控制器的效果进行了比较,证明了H∞控制应用于系统的优越性。     

时滞区间静态神经网络的全局鲁棒稳定性

应用Lyapunov泛函方法和拓扑度理论研究了时滞区间静态神经网络的全局鲁棒稳定性,给出了一些实用的判据。     

凸多面体不确定随机时滞系统的非脆弱鲁棒镇定

针对具有凸多面体不确定性的随机时滞系统，讨论了非脆弱鲁棒指数镇定问题，其中非脆弱控制器中的不确定性采用的是凸多面体不确定描述。基于Lyapunov直接法，采用了与参数相关的Lyapunov krasovskii泛函，并结合自由权矩阵方法, 使得Lyapunov矩阵与系统矩阵分离，从而获得了系统的完全基于线性矩阵不等式的时滞相关非脆弱鲁棒镇定的充分条件。最后,用例子说明了结果的有效性。     

Strategic Robust Mixed Model Assembly Line Balancing Based on Scenario Planning

Assembly line balancing involves assigning a series of task elements to uniform sequential stations with certain restrictions. Decision makers often discover that a task assignment which is optimal with respect to a deterministic or stochastic/fuzzy model yields quite poor performance in reality. In real environments, assembly line balancing robustness is a more appropriate decision selection guide. A robust model based on the α worst case scenario is developed to compensate for the drawbacks of traditional robust criteria. A robust genetic algorithm is used to solve the problem. Comprehensive computational experiments to study the effect of the solution procedure show that the model generates more flexible robust solutions. Careful tuning the value of α allows the decision maker to balance robustness and conservativeness of as- sembly line task element assignments.     

基于规范文本的特征词提取技术研究

文本特征词提取是一种提炼文本重要信息的实用技术,同时也为文本聚类、自动分类、信息抽取等相关课题提供了技术支持。在规范文本上,利用文本篇章结构的特征,以此为基础设计了一个特征词的加权函数,综合考虑了词频、词长和位置因子,并对比分析了各种位置因子对系统的贡献度。