Multivariable adaptive control: A survey

Adaptive control is a control methodology capable of dealing with uncertain systems to ensure desired control performance. This paper provides an overview of some fundamental theoretical aspects and technical issues of multivariable adaptive control, and a thorough presentation of various adaptive control schemes for multi-input–multi-output systems, literature reviews on adaptive control foundations and multivariable adaptive control methods, and related technical problems. It covers some basic concepts and issues such as certainty equivalence, stability, tracking, robustness, and parameter convergence. It discusses some of the most important topics of adaptive control: plant uncertainty parametrization, stable controller adaptation, and design conditions for different adaptive control schemes. The paper also presents a detailed study of well-developed multivariable model reference adaptive control theory and design techniques. It provides an introduction to multivariable adaptive pole placement and adaptive nonlinear control, and it concludes by identifying some open research problems.     

基于模板法制备两亲性Janus纳米粒子及其应用进展

Janus粒子是同一粒子中含有两种不同化学组成的非对称结构,其中两亲性Janus粒子是在对立面分别含有亲水基、疏水基两种不同化学基团,作为一种新型纳米材料受到广泛的关注。该文综述了模板法制备不对称结构的两亲性Janus粒子以及其应用领域,包括硬模板法、软模板法、牺牲模板法以及无模板法;综述了两亲性Janus粒子在表面活性剂、牙科粘合剂、微胶囊、功能涂层、催化剂以及生物传感器等方面的研究进展。     

Augment low-field intra-operative MRI with preoperative MRI using a hybrid non-rigid registration method

Background

Preoperatively acquired diffusion tensor image (DTI) and blood oxygen level dependent (BOLD) have been proved to be effective in providing more anatomical and functional information; however, the brain deformation induced by brain shift and tumor resection severely impairs the correspondence between the image space and the patient space in image-guided neurosurgery.

Method

To address the brain deformation, we developed a hybrid non-rigid registration method to register high-field preoperative MRI with low-field intra-operative MRI in order to recover the deformation induced by brain shift and tumor resection. The registered DTI and BOLD are fused with low-field intra-operative MRI for image-guided neurosurgery.

Results

The proposed hybrid registration method was evaluated by comparing the landmarks predicted by the hybrid registration method with the landmarks identified in the low-field intra-operative MRI for 10 patients. The prediction error of the hybrid method is 1.92 ± 0.54 mm, and the compensation accuracy is 74.3 ± 5.0%. Compared to the landmarks far from the resection region, those near the resection region demonstrated a higher compensation accuracy (P-value = .003) although these landmarks had larger initial displacements.

Conclusions

The proposed hybrid registration method is able to bring preoperatively acquired BOLD and DTI into the operating room and compensate for the deformation to augment low-field intra-operative MRI with rich anatomical and functional information.     

四丁基氢氧化胺模板磷酸铝对铬(Ⅵ)吸附性能的研究

研究了四丁基氢氧化胺模板磷酸铝对水中重金属离子铬(Ⅵ)的吸附特性。结果表明:四丁基氢氧化胺模板磷酸铝对铬(Ⅵ)吸附的最佳pH值和铬(Ⅵ)的初始质量浓度分别为2.0和40mg/L,且其吸附等温线符合Freundlich模型。     

柳州,云浮,宣化三厂预热分解系统技术改进经验引起的思考

本文分析了柳州、云浮、宣化三厂预分解系统粘结堵塞、难以稳定生产和不能“达产达标”的原因,逐一介绍了三厂预分解系统技术改进的措施和效果,并就其技改工程经验进行了分析总结和探索思考.     

纳米二氧化硅模板的制备

以微乳液法制备纳米二氧化硅（SiO2）粒子，经压制、烧结制备SiO2模板。通过红外（IR）、热分析（TGDTA）、扫描电镜（SEM）等方法对SiO2模板进行表征，结果表明所得SiO2粒度在100nm左右．烧结温度在800℃时，SiO2粒子之间将实现颈长，有利于有机／无机杂化多孔材料的制备。     

基于像素点的碎片图像拼接技术

针对一页规则的既纵切又横切的中文文件碎片和一页规则的双面打印的英文文件碎片,分别提出了一种基于行列图像的碎片匹配算法和二维图像成片连接匹配算法。首先将碎片边缘像素点转化成灰度值,然后对各碎片的灰度值进行匹配度研究,且将匹配度作为碎片之间拼接的依据,最后使用相应的算法计算机按碎片拼接顺序输出碎片号。通过实验分析表明,该算法能够更快地获得碎片拼接结果,大大提高拼接复原效率。     

变邻域分解多目标自适应差分进化算法

分解方法是处理复杂问题常用的一种手段,而差分进化算法被广泛地应用于多目标优化问题(multiobjective optimization problems,MOP),为了克服经典差分进化算法和分解方法的缺陷,本文提出了一种自适应差分进化算法和变邻域分解方法相结合的新颖算法一ADEMO/D-ENS,该算法采用Tchebycheff方法将多目标优化问题分解成多维标量优化子问题,并利用邻域子问题的信息进行优化,基于邻域种群集依概率自适应选择邻域种群规模;同时采用概率匹配(]probability match,PM)自适应方法从差分策略池中选择差分进化策略;同时分析了算法的复杂度;最后,通过和经典的非支配排序遗传算法(non-dominated sorting genetic algorithmsⅡ,NSGA-Ⅱ)和多目标差分进化算法(multi-objective differential evolution algorithm,MODE)仿真对比,说明ADEMO/D-ENS方法可以更有效的处理多目标优化问题.     

一种面向大规模短特征集的字符串匹配技术

面向大规模特征集的字符串匹配技术在病毒检测、内容过滤等问题上的应用愈加广泛,而短模式串一直是阻碍性能提升的重要瓶颈。针对短模式串进行分析讨论,基于跳跃算法优化,采用了动态块大小和动态Hash处理以及Hash函数设计场景化的策略,同时探讨了多核处理器与多线程设计之间的关系。实验数据证明改进的算法策略具有支撑百万级特征集字符串匹配的能力。