关联时滞大系统的H∞动态输出反馈控制——LMI方法

基于线性矩阵不等式方法 ,针对具有N×N个任意未知常时滞的线性连续大系统 ,给出了整个关联时滞大系统的H∞ 动态输出反馈控制器存在的充分条件和设计方法 .由该方法设计出的控制器不但使闭环系统渐近稳定而且保证闭环系统从扰动输入到被控输出的传递函数的H∞ 范数小于给定的常数γ .     

纤维复合相变材料的传热模型及性能分析

建立了纤维复合相变材料相变问题的焓求法求解传热模型,并用来求解复合相变材料在相变过程中流体温度和固－液相变界面随时间和空间的变化,籍此对相变蓄热材料的放热性能进行了模拟分析,为实用的纤维复合相变材料蓄热器的设计提供了依据。     

Necking Point in PET High-speed Fiber Spinning

Cross-over method is established to predict necking point for PET high-speed fiber spuming. Even slowly crystallizing polymers such as PET can crystallize on the spinline at sufficiently high spinning speed. The development of running velocity, temperature, crystallinity and rheological force is investigated for the take-up velocity over a range of 6 000 - 10 000 m/min. The pos-ition of necking point, temperature rise and abrupt increase of crystallinity move closer to the spinneret with the increase of take-up velocity.     

LMI Approach to Observer-based FD Systems Designing

Increasing the robustness to the unknown uncertainty and simultaneously enhancing the sensibility to the faults is one of the important issues considered in the fault detection development. Considering the L2-gain of residual system, this paper deals the observer-based fault detection problem. By using of H∞?control theory, an LMI approach to design fault detection observer is given. A numerical example is used to illustrate the effectiveness of the proposed approach.     

运动仿真在重型复杂机构多工位有限元建模中的应用

针对有限元分析软件的现有功能及其对重型复杂机构多工位建模工作量大的特点,本文将多刚体系统运动仿真理论和方法运用到结构有限元建模中,并结合实例说明了多刚体系统运动仿真与结构有限元分析相结合的方法及该方法的有效性。     

钢丝绳索力自动化检测系统的设计

提出了采用磁阻式传感器的方式拾取钢丝绳振动信号的思想,设计出传感器的结构和对传感信号进行放大,滤波处理的电路,在单片机8031和个人计算机的控制下,实现了用8位A／D转换器对信号进行A/D转换,考虑到信号有有用成分频率较低,采用计算与单片机8031进行实时串行通讯的方式把A／D转换结果送入到计算机中,并利用计算机丰富的软件资源和快速的计算功能对采样数据应用快速傅立叶变换方式进行频谱分析,把求得的功率谱最大谱值所对应的频率作为钢丝绳的固有频率,最后,根据钢丝绳内力与其固有频率这间的内在关系,计算钢丝绳当前所受的拉力。     

Exploration of TCM Masters Knowledge Mining

Traditional Chinese medicine （TCM） has a rich knowledge about human health and disease by its special way evolved along a very long history. As modern medicine is achieving much progress, arguments and disputes toward TCM never end. To avoid losing precious knowledge of living TCM masters, endeavors have been engaged to systematic collection of those knowledge of TCM masters, such as their growth experiences, effective practical cases toward diseases and typical therapeutic principles and methods. Knowledge mining methods have been expected to explore some useful or hidden patterns to unveil some mysteries of the TCM system. In the paper, some computerized methods are applied toward those collected materials about some living TCM masters in China mainland to show a different way of exposing essential ideas of those TCM masters by correspondence visualization which aims to help people understand TCM holistic views toward disease and body, and facilitate tacit knowledge transfer and sense-making of the essence of TCM. The work is one kind of qualitative meta-synthesis of TCM masters＇ knowledge.     

Data association based on target signal classification information

In most of the passive tracking systems, only the target kinematical information is used in the measurement-to-track association, which results in error tracking in a multitarget environment, where the targets are too close to each other. To enhance the tracking accuracy, the target signal classification information （TSCI） should be used to improve the data association. The TSCI is integrated in the data association process using the JPDA （joint probabilistic data association）. The use of the TSCI in the data association can improve discrimination by yielding a purer track and preserving continuity. To verify the validity of the application of TSCI, two simulation experiments are done on an air target-tracing problem, that is, one using the TSCI and the other not using the TSCI. The final comparison shows that the use of the TSCI can effectively improve tracking accuracy.     

Krylov subspace method based on data preprocessing technology

The performance of adaptive beamforming techniques is limited by the nonhomogeneous clutter scenario. An augmented Krylov subspace method is proposed, which utilizes only a single snapshot of the data for adaptive processing. The novel algorithm puts together a data preprocessor and adaptive Krylov subspace algorithm, where the data preprocessor suppresses discrete interference and the adaptive Krylov subspace algorithm suppresses homogeneous clutter. The novel method uses a single snapshot of the data received by the array antenna to generate a cancellation matrix that does not contain the signal of interest （SOI） component, thus, it mitigates the problem of highly nonstationary clutter environment and it helps to operate in real-time. The benefit of not requiring the training data comes at the cost of a reduced degree of freedom （DOF） of the system. Simulation illustrates the effectiveness in clutter suppression and adaptive beamforming. The numeric results show good agreement with the proposed theorem.     

Research on the self-defence electronic jamming decision-making based on the discrete dynamic Bayesian network

The manner and conditions of running the decision-making system with self-defense electronic jamming are given.After proposing the scenario of applying discrete dynamic Bayesian network to the decision making with self-defense electronic jamming,a decision-making model with self-defense electronic jamming based on the discrete dynamic Bayesian network is established.Then jamming decision inferences by the aid of the algorithm of discrete dynamic Bayesian network are carried on.The simulating result shows that this method is able to synthesize different targets which are not predominant.In this way,various features at the same time,as well as the same feature appearing at different time complement mutually;in addition,the accuracy and reliability of electronic jamming decision making are enhanced significantly.