一种基于混合量子粒子群的快速运动目标跟踪算法研究

量子粒子群算法在优化过程中需要权衡局部探索性和全局开拓性,进化后期由于全局开拓能力的丧失使得种群多样性减少,设计了一种基于欧式距离的混合量子粒子群算法,通过计算粒子的种群多样性,当种群多样性低于阈值范围时加入基于欧式距离的种群划分策略划分子种群,从而保证获得全局最优解。利用标准测试函数验证提出的混合量子群算法有效性。提出了基于混合量子粒子群的Mean Shift算法(HQPSO Mean Shift)完成目标快速跟踪,克服传统Mean Shift算法的在跟踪快速移动目标时出现"跟丢"的问题。     

一种卡尔曼增益约束滤波算法

在滤波过程中,将卡尔曼增益结合约束条件,可以有效地提高滤波精度.论文推导了含有卡尔曼增益约束条件的代价函数,根据Karush-Kuhn-Tucker（KKT）最小化的一阶必要条件,使用高斯牛顿法求出约束卡尔曼增益的最优约束解.最后对具有约束条件的目标跟踪问题进行了仿真实验,结果表明该算法的跟踪精度要高于普通卡尔曼滤波算法.     

基于体感技术的手势追踪与识别

体感技术使人们更直接的通过自己的肢体动作与电脑设备产生互动,减小了鼠标、键盘等传统输入设备带来的束缚。使用Kinect 体感设备,对体感关键技术及 Kalman滤波器算法进行了深入的研究,并在此基础上提出了一种基于骨骼坐标的手势识别算法。最后详细阐明了基于 Kinect 的手势追踪与识别系统的具体设计与实现方法。     

基于话题检测的自适应增量K-means算法

根据话题检测任务的定义和特点,本文分析了传统的增量聚类算法和K-means算法的优缺点,提出了基于话题检测的自适应增量K-means算法,设计了话题检测实验,实验结果证明了该算法提高了话题检测性能,具有良好的应用前景。     

跟踪微分器在生物雷达中的应用

在探测废墟下存活的人体时,生物雷达很难找到理想的参考信号对采集的信号进行处理.对已有生物雷达信号处理方法性能分析,提出了基于微分跟踪器（TD）的信号处理方法.该方法不需要理想的信号作为参考信号,且收敛性能和鲁棒性好、稳态误差小.MATLAB仿真分析证明了该算法应用于生物雷达信号处理的有效性.     

网络冗余技术在公司局域网的应用分析

随着SG186系统建设不断向企业的覆盖与延伸,信息网络的强健与否成为制约信息化系统应用的重要因素。本文通过对网络冗余技术的介绍,结合公司信息网络结构实际情况,通过应用实例分析,阐述如何合理使用网络冗余技术,确保信息网络的高可靠性。     

A quantitative feedback solution to the multivariable tracking error problem

This paper introduces a novel solution for the multi‐input multi‐output (MIMO) quantitative feedback theory control design problem with tracking error specifications. Looking for a minimum controller overdesign, the technique finds new controller quantitative feedback theory bounds based on necessary and sufficient conditions for the existence of suitable associated prefilter matrix elements. It improves previous approaches to the subject and includes (i) the possibility of a free selection of the nominal plant, (ii) a less conservative application of the Schwartz inequality to decisively reduce the potential controller overdesign, (iii) a methodology to design independently the elements of the prefilter matrix, and (iv) a scope of application to both sequential and nonsequential MIMO controller design methods. The benefits of the new control design technique are illustrated by means of two examples. The first one, a standard 2 × 2 MIMO problem, is provided for comparison purposes with previous approaches. The second example, included as a major control challenge, deals with a well‐known demanding distillation column benchmark problem. Copyright © 2013 John Wiley & Sons, Ltd.     

An embedding approach for the design of state‐feedback tracking controllers for references with jumps

We study the problem of designing state‐feedback controllers to track time‐varying state trajectories that may exhibit jumps. Both plants and controllers considered are modeled as hybrid dynamical systems, which are systems with both continuous and discrete dynamics, given in terms of a flow set, a flow map, a jump set, and a jump map. Using recently developed tools for the study of stability in hybrid systems, we recast the tracking problem as the task of asymptotically stabilizing a set, the tracking set, and derive conditions for the design of state‐feedback tracking controllers with the property that the jump times of the plant coincide with those of the given reference trajectories. The resulting tracking controllers guarantee that solutions of the plant starting close to the reference trajectory stay close to it and that the difference between each solution of the controlled plant and the reference trajectory converges to zero asymptotically. Constructive conditions for tracking control design in terms of LMIs are proposed for a class of hybrid systems with linear maps and input‐triggered jumps. The results are illustrated by various examples. Copyright © 2013 John Wiley & Sons, Ltd.     

基于可控电抗器的单调谐滤波器的两种控制方法比较

可控电抗器作为电力设备中常用的一种非线性装置,其控制方式直接影响设备的整体性能.本文从可控电抗器的控制特性出发,阐述了基于可控电抗器的单调谐滤波器的两种控制方法,即相位跟踪控制法和自寻最优控制法.比较了两种方法在110V工作电压下的控制效果及各自的应用环境.     

一种基于模糊神经网络的机器人轨迹跟踪控制

提出一种模糊神经网络,并将其应用于两关节机械手轨迹跟踪控制。该网络采用三角形隶属度函数,将模糊控制与神经网络相结合,利用神经网络实现模糊推理。这种模糊神经网络能够在线调节输出隶属度函数中心以及关节间耦合权值,使得控制器具有更好的学习与自适应能力。仿真结果表明,这种网络能很好的用于机器人的轨迹跟踪控制中,是一种行之有效的控制方法。