Adaptive tracking control of an autonomous underwater vehicle

This paper presents the trajectory tracking control of an autonomous underwater vehicle(AUV). To cope with parametric uncertainties owing to the hydrodynamic effect, an adaptive control law is developed for the AUV to track the desired trajectory. This desired state-dependent regressor matrix-based controller provides consistent results under hydrodynamic parametric uncertainties.Stability of the developed controller is verified using the Lyapunov s direct method. Numerical simulations are carried out to study the efficacy of the proposed adaptive controller.     

一种用于目标跟踪的波形自适应选择算法

提出了一种用于雷达目标跟踪的自适应广义调频波形设计算法。该算法根据跟踪器的动态需求,以广义调频信号为样板波形自适应设计下一时刻的发射波形,其目的是最小化预测的目标跟踪均方误差,并假定高信噪比条件,且目标跟踪运动模型和观测模型均为线性,利用与某一波形相对应的克拉美--罗下限（CRLB）以及卡尔曼滤波器,通过最小化预测的跟踪均方误差来实现广义调频波形的自适应设计。仿真结果表明：在信噪比相同的情况下,与使用固定参数、自适应参数的线性调频波形设计算法相比,所提出的算法能够获得更低的目标跟踪均方误差。     

基于密度调整的改进自适应谱聚类算法

针对谱聚类存在构造相似度矩阵时对尺度参数敏感以及处理多重尺度数据集效果不理想的缺陷, 提出一种基于密度调整的改进自适应谱聚类算法. 该算法将样本点所处领域的密度引入谱聚类, 利用密度差来调整样本点之间的相似度, 使其更符合实际簇类中样本点间的内在关系, 在一定程度上解决了多尺度聚类问题; 同时, 通过样本点的近邻距离自适应得到尺度参数, 使算法对尺度参数相对不敏感. 仿真实验验证了所提出算法的有效性和优越性.

     

Adaptive Face Recognition via Structed Representation

In this paper, we propose a face recognition approach-Structed Sparse Representation-based classification when the measurement of the test sample is less than the number training samples of each subject. When this condition is not satisfied, we exploit Nearest Subspaee approach to classify the test sample. In order to adapt all the eases, we combine the two approaches to an adaptive classification method-Adaptive approach. The adaptive approach yields greater recognition accuracy than the SRC approach and CRC_RLS approach with low ~ample rate on the Extend Yale B dataset. And it is more efficient than other two approaches.     

One-shot methods in function space for PDE-constrained optimal control problems

We state and analyse one-shot methods in function space for the optimal control of nonlinear partial differential equations (PDEs) that can be formulated in terms of a fixed-point operator. A general convergence theorem is proved by generalizing the previously obtained results in finite dimensions. As application examples we consider two nonlinear elliptic model problems: the stationary solid fuel ignition model and the stationary viscous Burgers equation. For these problems we present a more detailed convergence analysis of the method. The resulting algorithms are computationally implemented in combination with an adaptive mesh refinement strategy, which leads to an improvement in the performance of the one-shot approach.     

A sum of squares approach to backstepping controller synthesis for piecewise affine and polynomial systems

This paper develops a backstepping controller synthesis methodology for piecewise polynomial (PWP) systems in strict form. The main contribution of the paper is to formulate sufficient conditions for controller design for PWP systems in strict form as a sum of squares feasibility problem under the assumption that an initial control Lyapunov function exists to start the iterative backstepping procedure. This problem can then be translated into a convex SDP problem and solved by available software packages. The controller synthesis problem for PWP systems in strict feedback form is divided into two cases. The first case consists of the construction of a sum of squares polynomial control Lyapunov function for PWP systems with discontinuous vector fields. The second case addresses the construction of a PWP control Lyapunov function for PWP systems with continuous vector fields. One major advantage of the proposed method is the fact that it can handle systems with discontinuous vector fields and sliding modes. The new synthesis method is applied to several numerical examples. One of these examples offers the first convex optimization solution to piecewise affine (PWA) control of a benchmark circuit system addressed before in the literature using non‐convex PWA control solutions. Copyright © 2013 John Wiley & Sons, Ltd.     

基于对称KL距离的自适应粒子滤波算法

针对粒子滤波算法中粒子数自适应的问题,提出了一种新的算法.将当前滤波时刻的粒子随机划分为粒子数相同的两个粒子群,并采用对称KL距离方法计算他们之间的信息距离,然后根据信息距离的大小决定增加或者减少下一时刻参与滤波的粒子数,从而实现了滤波过程中粒子数目的自适应.该方法在确保一定滤波精度的基础上,能够减少滤波过程中需要的粒子数,为降低粒子滤波算法的时间复杂度提供了新的途径.仿真结果表明了算法的有效性.     

Vehicle Dynamics Modeling and Simulation for ACC

A 7 degree-of-freedom (DOF) 4 wheels vehicle dynamics model based on Matlab-Simulink is established,and 7 DOF vehicle dynamics equations in the form of nonlinear state-space standards are given.The characters of the electronic throttle and the active braking system have been analyzed.And the electronic throttle model and the active braking system model are built according to the test results respectively.Off-line simulation results indicate that the model is suitable for the vehicle adaptive cruise control ...     

3-D direct current resistivity forward modeling by adaptive multigrid finite element method

Based on the fact that 3-D model discretization by artificial could not always be successfully implemented especially for large-scaled problems when high accuracy and efficiency were required, a new adaptive multigrid finite element method was proposed. In this algorithm, a-posteriori error estimator was employed to generate adaptively refined mesh on a given initial mesh. On these iterative meshes, V-cycle based multigrid method was adopted to fast solve each linear equation with each initial iterative term interpolated from last mesh. With this error estimator, the unknowns were nearly optimally distributed on the final mesh which guaranteed the accuracy. The numerical results show that the multigrid solver is faster and more stable compared with ICCG solver. Meanwhile, the numerical results obtained from the final model discretization approximate the analytical solutions with maximal relative errors less than 1%, which remarkably validates this algorithm.