Structured H∞‐control of infinite‐dimensional systems

We develop a novel frequency‐based H_∞‐control method for a large class of infinite‐dimensional linear time‐invariant systems in transfer function form. A major benefit of our approach is that reduction or identification techniques are not needed, which avoids typical distortions. Our method allows to exploit both state‐space or transfer function models and input/output frequency response data when only such are available. We aim for the design of practically useful H_∞‐controllers of any convenient structure and size. We use a nonsmooth trust‐region bundle method to compute arbitrarily structured locally optimal H_∞‐controllers for a frequency‐sampled approximation of the underlying infinite‐dimensional H_∞‐problem in such a way that (i) exponential stability in closed loop is guaranteed and that (ii) the optimal H_∞‐value of the approximation differs from the true infinite‐dimensional value only by a prior user‐specified tolerance. We demonstrate the versatility and practicality of our method on a variety of infinite‐dimensional H_∞‐synthesis problems, including distributed and boundary control of partial differential equations, control of dead‐time and delay systems, and using a rich testing set.     

Lebesgue-?? 范数意义下对初态误差进行加速修正的迭代学习控制

针对一类多输入多输出线性时不变系统, 提出一种初态误差加速修正的PD-型迭代学习算法. 针对系统的任意初始状态, 在时间轴上设计一个随迭代次数增加而缩短的修正区间. 在该区间上, 控制算法对初始状态偏差进行修正; 修正区间外, 算法与无初始误差的学习律等同. 在Lebesgue-?? 范数度量跟踪误差意义下, 利用卷积的推 广Young 不等式证明了所提出学习控制律的收敛性. 数值仿真验证了该控制律的有效性.

     

基于样本选取和加权KPCA-L1的异常检测*

为了提高基于一范数的核主成分分析算法（KPCA-L1）处理异常检测问题的速度,提出了基于样本选取和加权KPCA-L1的异常检测方法。所提方法首先从训练集中选取具有代表性的特征子集,然后为所得特征子集中的样本赋予权重,用带有权重的特征子集训练模型,构造加权KPCA-L1。与KPCA-L1相比,所提方法能够有效地减小训练集的规模,同时改善了KPCA-L1算法的更新方法。在人工数据集和标准数据集上的实验结果表明,在保证异常检测准确率的前提下,所提方法比KPCA-L1具有更快的建模速度。     

具有时滞和时变系数的离散多智能体系统的一致性

研究一类具有时滞和时变系数的离散多智能体系统的一致性问题. 首先, 通过构造合适的控制协议, 并以第一个智能体的位移作为参考状态, 将原系统的一致性问题转化为误差系统中零解的渐近稳定性问题; 然后, 运用矩阵范数理论研究误差系统零解的渐近稳定性, 导出使多智能体系统实现一致的充分条件; 最后, 通过数值模拟验证了该判据的正确性和有效性.

     

基于最大变差范数准则的ISAR自聚焦方法

为消除目标平动引起的初相误差,必须进行自聚焦以避免ISAR图像模糊.在分析ISAR回波信号模型的基础上,本文构造了高阶多项式相位信号的初相补偿函数.已有文献多ISAR图像聚焦程度为准则,对该多项式相位信号的参数进行优化.本文利用最大全变差范数作为ISAR方位向成像的聚焦评价准则,该指标值在平动参数空间中的分布具有局部极值点少的优点,利于最优确定初相补偿函数的参数,并采用协同粒子群优化算法加速参数的寻优速度和精度.仿真实验证明了本文方法的可行性和正确性.     

基于直觉模糊三角模的直觉模糊粗糙集

提出一种基于直觉模糊三角模的直觉模糊粗糙集.首先,定义了直觉模糊集上的T模及其剩余蕴涵,研究了直觉模糊T模的剩余蕴涵的性质,并推导了通用计算表达式;然后,将模糊T粗糙集扩展成直觉模糊粗糙集,证明了模糊T粗糙集、粗糙模糊集和Pawlak粗糙集都是直觉模糊粗糙集的特殊情形;最后,证明了直觉模糊粗糙集的一些性质.     

Why do we trust new technology? A study of initial trust formation with organizational information systems

Recent trust research in the information systems (IS) field has described trust as a primary predictor of technology usage and a fundamental construct for understanding user perceptions of technology. Initial trust formation is particularly relevant in an IS context, as users must overcome perceptions of risk and uncertainty before using a novel technology. With initial trust in a more complex, organizational information system, there are a number of external determinants, trusting bases, that may explain trust formation and provide organizations with the needed levers to form or change individuals’ initial trust in technology. In this study, a research model of initial trust formation is developed and includes trusting bases, trusting beliefs, trusting attitude and subjective norm, and trusting intentions. Eight trusting base factors are assessed including personality, cognitive, calculative, and both technology and organizational factors of the institutional base. The model is empirically tested with 443 subjects in the context of initial trust in a national identity system (NID). The proposed model was supported and the results indicate that subjective norm and the cognitive–reputation, calculative, and organizational situational normality base factors significantly influence initial trusting beliefs and other downstream trust constructs. Factors from some of the more commonly investigated bases, personality and technology institutional, did not significantly affect trusting beliefs. The findings have strategic implications for agencies implementing e-government systems and organizational information systems in general.     

具有测量数据丢失的网络化系统的故障检测滤波

研究一类具有测量数据部分丢失的网络化系统的故障检测滤波器设计问题. 测量数据的丢失假设满足已知概率的Bernoulli分布. 设计一个故障检测滤波器, 使残差误差系统均方指数稳定且具有一定的扰动衰减水平. 采用线性矩阵不等式方法, 给出了故障检测滤波器存在的充分条件. 最后通过例子说明该方法的有效性.     

直觉模糊逻辑算子研究’

模糊逻辑算子是模糊信息融合、模糊推理及模糊决策的重要工具。针对作为模糊逻辑算子重要扩展的直觉模糊逻辑算子,首先引入了直觉模糊集在特殊格上的等价定义。其次,验证了直觉模糊t-模与s-模的若干重要性质。在此基础上,对两种常用的蕴涵算子：直觉模糊孓蕴涵与直觉模糊R-蕴涵所具有的新性质进行讨论和证明,从而便于直觉模糊逻辑算子的进一步应用。     

直觉模糊三角模的剩余蕴涵及其性质

研究了直觉模糊三角模的剩余蕴涵及其性质。首先,定义了直觉模糊三角模的剩余蕴涵;其次,推导了直觉模糊三角模的剩余蕴涵与三角模的剩余蕴涵的关系;最后,证明了直觉模糊三角模的剩余蕴涵的16条性质。直觉模糊三角模的剩余蕴涵及其性质在直觉模糊推理、群决策等领域具有广阔的应用前景。