Adaptive control for switched uncertain nonlinear systems with time‐varying output constraint and input saturation

This paper is concerned with adaptive tracking control for switched uncertain nonlinear systems, which contain the time‐varying output constraint (TVOC) and input asymmetric saturation characteristic. In response to the unknown functions, the fuzzy logic systems are adopted. The controller is constructed by the backstepping technique. Based on the Tangent Barrier Lyapunov Function (BLF‐Tan), an adaptive switched control scheme is designed. It is demonstrated that all signals in the resulted system are semiglobally uniformly ultimately bounded with TVOC under arbitrary switchings. Furthermore, the effectiveness of presented control method is validated via the simulation example.     

融入局部几何特征的流形谱聚类图像分割

为了改善谱聚类图像分割的精准性和时效性,文中提出融入局部几何特征的流形谱聚类图像分割算法.首先,考虑图像数据的流形结构,在数据点的K近邻域内执行局部PCA,得到数据间本征维数的关系.然后,引入流形学习中的局部线性重构技术,通过混合线性分析器得到数据间局部切空间的相似性,结合二者构造含有局部几何特征的相似性矩阵.再利用Nystr m技术逼近待分割图像的特征向量,对构造的k个主特征向量执行谱聚类.最后,在Berkeley数据集上的对比实验验证文中算法的准确性和时效性优势.     

Comparison and improvement of tangent estimators on digital curves

Many contour-based applications rely on the estimation of the geometry of the shape, such as pattern recognition or classification methods. This paper proposes a comprehensive evaluation on the problem of tangent estimators on digital curves. The methods taken into account use different paradigms: approximation and digital geometry. In the former paradigm, methods based on polynomial fitting, smoothing and filtering are reviewed. In the latter case of digital geometry, we consider two methods that mainly rely on digital straight line recognition [J.-O. Lachaud, A. Vialard, F. de Vieilleville, Fast, accurate and convergent tangent estimation on digital contours, Image and Vision Computing 25(10) (2007) 1572-1587] and optimization [B. Kerautret, J.-O. Lachaud, Robust estimation of curvature along digital contours with global optimization, in: Proceedings of Discrete Geometry for Computer Imagery, Lyon, France, Lecture Notes in Computer Science, vol. 4992, Springer, Berlin, 2008]. The comparison takes into account objective criteria such as multi-grid convergence, average error, maximum error, isotropy and length estimation. Experiments underline that adaptive methods based on digital straight line recognition often propose a good trade-off between time and precision and that if precision is to be sought, non-adaptive methods can be easily transformed into adaptive methods to get more accurate estimations.     

Adaptive and optimal difference operators in image processing

Differential operators are essential in many image processing applications. Previous work has shown how to compute derivatives more accurately by examining the image locally, and by applying a difference operator which is optimal for each pixel neighborhood. The proposed technique avoids the explicit computation of fitting functions, and replaces the function fitting process by a function classification process using a filter bank of feature detection templates. Both the feature detectors and the optimal difference operators have a specific shape and an associated cost, defined by a rigid mathematical structure, which can be described by Gröbner bases. This paper introduces a cost criterion to select the operator of the best approximating function class and the most appropriate template size so that the difference operator can be locally adapted to the digitized function. We describe how to obtain discrete approximates for commonly used differential operators, and illustrate how image processing applications can benefit from the adaptive selection procedure for the operators by means of two example applications: tangent computation for digitized object boundaries and the Laplacian of Gaussian edge detector.     

分配曲线经验模型在预测和优化中的应用

重力选煤的预测与优化都是利用分配率的计算来实现的。分配曲线经验模型应用于预测和优化的关键是解决模型参数与分选密度间的变换关系。通过实际预测计算，分析了当前广泛应用的几种分配曲线的经验模型在预测应用中误差较大的原因。并针对复合双曲正切模型，提出了一套模型参数变换公式，通过与其它多种经验模型的对比验证，证明复合双曲正切模型可以更为准确的用于重力选的预测和优化。     

利用AutoCAD2000绘制三轴剪切线包络线图

介绍了利用AutoCAD2000绘制土工试验三轴剪切线包络线图的作业方法，并结合工程实例对作业过程中的窗口和菜单操作及参数设置等作了具体说明。     

Boosting Ensemble Learning for Hyperspectral Image Classification Using Tangent Collaborative Representation

Recently, Collaborative Representation Classification (CRC) has attracted much attention in hyperspectral image analysis. Due to uses the tangent plane to estimate the local manifold of the test sample. Tangent Collaborative Representation Classification (TCRC) achieve better performance. Furthermore, in order to improve the classification accuracy and reliability of hyperspectral remote sensing images, a novel Boosting-based Tangent Collaborative Representation ensemble method (Boost TCRC) for hyperspectral image classification is proposed. In this algorithm, Boost TCRC algorithm choose TCRC as base classifier and adjust the weight of the training samples adaptively by using the principle of Boosting. Increasing the weight of the misclassified samples so that the classifier concentrates on the training samples that are difficult to classify. Then assigns the weights according to the classification performance of the base classifier based on the residual domain fusion. Finally, the principle of minimum reconstruction error is adopted to classify the test sample. The performance of the proposed algorithm was comprehensively evaluated by hyperspectral remote sensing image data such as HyMap (Hyperspectral Mapper) and AVIRIS (Airbone Visible Infrared Imaging Spectrometer). The Boosting method can effectively improve the classification effect of the TCRC algorithm. For HyMap data, the overall classification accuracy and kappa coefficient of Boost TCRC algorithm are 93.73% and 0.920 8 respectively. Two precision values are higher than TCRC algorithm by 2.82% and 0.032 3, and are higher than the AdaBoost ELM algorithm by 1.81% and 0.022 5. For AVIRIS data, the overall classification accuracy and kappa coefficient of Boost TCRC algorithm are 84.11% and 0.8120 respectively. Two precision values are higher than TCRC algorithm by 3.97% and 0.049 3, and are higher than AdaBoost ELM algorithm by 12.02% and 0.143 6.     

多新息模型辨识PMSM双曲正切滑模定位控制

永磁同步电机伺服系统是一个复杂的非线性系统,模型参数、摩擦等因素使其难以用准确的数学模型表示。针对永磁同步电机伺服系统存在不确定参数、摩擦及外部扰动现象,提出一种基于多新息模型辨识的双曲正切滑模定位策略。首先,将永磁同步电机的模型进行状态离散化,并用多新息模型辨识方法对系统的模型参数进行辨识;然后根据离散化的辨识系统状态空间模型,设计一种双曲正切滑模控制器;同时,基于Lypunov理论对设计的闭环控制系统进行稳定性分析;最后通过数值仿真验证这里方法的正确性和有效性。     

Are linear prebuckling paths and linear stability problems mutually conditional?

Stability problems are termed linear if the tangent stiffness used for determining loss of stability has a specific, simple form. The term “linear prebuckling paths” refers to the shape of the load–displacement diagrams before loss of stability. In this note, it will be shown that these two terms are not mutually conditional.     

浅析CVT电容分压器在10kV下的介质损耗角正切

主要分析了CVT电容分压器在10kV和Un下的损耗角正切(tanδ)之间的关系,影响电容分压器10kV下的tanδ的因素,其中着重分析tanδ与真空干燥处理工艺之间的关系。并提出了降低tanδ的若干技术措施。