多变量系统状态空间模型的递阶辨识

研究多变量系统状态空间模型的递阶辨识问题,推广了作者提出的标量系统状态和参数联合辨识算法.当状态可量测时,利用最小二乘原理直接辨识状态空间模型的参数矩阵;当状态不可测时,利用递阶辨识原理提出了状态空间模型递阶辨识方法,使用系统输入输出数据来估计系统的未知状态和参数.状态空间模型递阶辨识方法分为两步:首先假设系统状态是已知的(即参数估计算法中的未知系统状态用其估计代替),基于状态估计和系统输入输出数据递归计算系统参数估计;然后基于系统输入输出数据和获得的参数估计,递归计算系统的状态估计.     

Fault diagnosis based on high-gain observer with an update law for a class of nonlinear systems

In this paper, by using the well-known high-gain observer design, an update law for the gain and an adaptive estimation of parameters, a new method of fault diagnosis for a class of nonlinear systems is presented. Without resort to any transformation for the parameters, the estimation errors of the states and the parameters are guaranteed to be globally exponentially convergent by a persistent excitation condition. Compared to the existing results, it can be applied to nonlinear systems with nonlinear terms admitting an incremental rate depending on the measured output. A case study further verifies the validity of the proposed research.     

基于云模型的指挥信息多重协同过滤算法研究

针对传统协同过滤算法在构建指挥员与指挥要素间的协同过滤关系时面临着数据稀疏、冷启动等问题,提出了一种面向反恐任务的指挥信息多重协同过滤算法。该算法首先通过作战类型对指挥要素进行基于云模型的预协同过滤,然后将凝聚子集分析融入基于用户的协同过滤中,挖掘特定战斗类型下的指挥员与指挥要素间的相似性关系,进而实现精准推荐。实验表明,该算法贴合面向作战任务的指挥信息系统应用实践,有效提高了系统的推荐效率和准确度。     

一种将需求模型转换为软件体系结构模型的方法

需求模型到软件体系结构(SA)模型的转换是软件工程领域的一个研究热点。针对DERM所建立的ACP风格的需求模型,以扩展Petri网风格的SA模型为模型转换的目标,以行为映射为模型转换的依据,提出了一种将需求模型转换为SA模型的方法。首先,讨论了模型转换的整体思路;其次,将行为特征模型中的各个结点转换为SA模型中的构件和连接件,并提出了相应的转换规则;再次,讨论了属性特征模型中主动属性特征的转换,并提出了子系统划分的策略;最后,通过案例研究展示了该方法在从需求模型到SA模型的转换中的有效性。     

Robust fuzzy tracking control for nonlinear networked control systems with integral quadratic constraints

This paper investigates the robust tracking control problem for a class of nonlinear networked control systems (NCSs) using the Takagi-Sugeno (T-S) fuzzy model approach. Based on a time-varying delay system transformed from the NCSs, an augmented Lyapunov function containing more useful information is constructed. A less conservative sufficient condition is established such that the closed-loop systems stability and time-domain integral quadratic constraints (IQCs) are satisfied while both time-varying network-induced delays and packet losses are taken into account. The fuzzy tracking controllers design scheme is derived in terms of linear matrix inequalities (LMIs) and parallel distributed compensation (PDC). Furthermore, robust stabilization criterion for nonlinear NCSs is given as an extension of the tracking control result. Finally, numerical simulations are provided to illustrate the effectiveness and merits of the proposed method.     

基于惯性权重非线性动态变化的微粒群算法

本文提出一种惯性权重非线性动态变化的微粒群算法(NDPSO),根据微粒在群体中距群体最优位置的远近,选择不同的惯性权重非线性下降指数,每个微粒根据个体状况选择不同的惯性权重.在NDPSO算法中,距最优位置较远区域惯性权重选择较小的下降指数,这样利于微粒较快地飞向群体最优位置,提高算法的全局搜索性能;当微粒飞到距最优位置较近区域时,惯性权重采用较大的下降指数,这样微粒在此区域进行细致的搜索,提高算法的收敛速度.为了研究NDPSO算法的性能,对几种典型高维非线性函数进行了测试.测试结果表明,与其它几种典型的微粒群算法相比,NDPSO明显地提高了算法的性能.     

一种新型三极交流磁轴承原理与解耦控制

摘要：阐述了一种新型三极交流磁轴承的基本结构与工作原理,用等效磁路法推导了其悬浮力数学模型。针对三极交流磁轴承在两相静止坐标系下数学模型的强耦合特性,采用逆系统方法将其解耦为伪线性系统,并在该伪线性系统的基础上利用线性二次型调节器（Linear Quadratic Regulator,简称LQR）设计了满足性能指标的控制器。仿真试验表明这种解耦控制策略不仅能够实现三极交流磁轴承径向位移之间的动态解耦,而且可以实现转子稳定悬浮,并且系统具有良好的动、静态性能。     

Improving the Management of Endometrial Cancer Patients through the Use of Liquid Biopsy Analyses: A Case Report

Endometrial cancer (EC) is the 4th most common neoplasm of the female genital tract, with 15–20% of patients being of high risk of recurrence which leads to a significant decrease in patient survival. Current therapeutic options for patients with EC are poor, being the combined therapy of carboplatin and paclitaxel the standard of care, with limited efficacy. Therefore, new therapeutic options and better monitoring tools are needed to improve the management of the disease. In the current case report, we showcase the value of liquid biopsy analyses in a microsatellite instability EC patient with initially good prognosis that however underwent rapid progression disease within 6 months post-surgery; through the study of plasma cfDNA/ctDNA dynamics to assess the tumour evolution during treatment, as well as the study of the uterine aspirate as a valuable sample that captures the intra-tumour heterogeneity that allows a comprehensive genomic profiling of the disease to identify potential therapeutic options. Furthermore, preclinical models were generated at the time of tumour progression to assess the efficacy of the identified targeted therapies.     

Systematic Review: Drug Repositioning for Congenital Disorders of Glycosylation (CDG)

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders’ views on AI for therapy discovery in CDG.     

管壳式换热器流体与传热模拟分析

利用solidworks建立管壳式换热器的物理模型,并导入ANSYS 12.0中进行流体与热传导模拟分析。设置冷水和热水不同的入口速度,可得出热量的传递和分布规律、流动形态的不同。设置冷水和热水不同的温差,可得出不同温差条件下换热器内的温度分布和变化规律。对换热器结构优化和提高传热效率有一定的参考价值。