Optimal Performance in Tracking Stochastic Signal Under Disturbance Rejection

The analysis method of optimal tracking performance is proposed for multiple‐input multiple‐output (MIMO) linear time‐invariant (LTI) systems under disturbance rejection. An H₂ criterion of the error signal between the output of the plant and the reference signal is used as a measure for the tracking performance. Spectral factorization is applied to obtain the optimal solution of the system tracking error. The explicit expressions are derived for this minimal tracking error with respect to random reference signals under disturbance rejection. It is shown that the nonminimum phase zeros, the zero direction, the unstable poles, the pole direction of a given plant, statistical characteristics of the reference input signal, and disturbance signal have a negative effect on a feedback system's ability to reduce the system error with disturbance rejection. The results show that the optimal tracking performance will further be damaged because of disturbance rejection. Some typical examples are given to illustrate the theoretical results.     

变风量空调系统优化控制策略研究

变风量空调系统是多变量,大滞后、非线性和不确定性的系统,普通的模糊神经网络控制已难以满足其多变量动态控制的要求,为改善变风量空调系统控制性能,本文提出了一种小波模糊神经网络预测控制方法,实现变风量空调的温湿度有效控制.通过小波神经网络预测器在线建立被控对象的数学模型,并用模糊RBF神经网络控制器对所得到的信息在线修正,优化控制器参数,从而改善系统的控制效果.仿真结果表明,小波模糊神经网络预测控制具有很强的鲁棒性和自适应能力,控制精度高,控制效果好,安全可靠等优点,具有广泛的应用价值.     

基于内容的静态语义概念视频检索方法研究

本文针对互联网视频检索技术的发展,阐述了目前主流视频搜索引擎的技术现状,分析了互联网视频检索的关键技术,特别是对于视频特征的提取技术。本文的创新点是提出了一种通用的基于内容的静态语义视频检索方法,该方法可以弥补基于文本视频检索的有关不足,并且在TRECVID的视频概念检索数据的静态语义概念中得到验证,运行稳定。     

冲击荷载作用下热处理花岗岩动态力学特性研究

为研究冲击速度和热处理温度对黑云母花岗岩动态力学特性的影响,利用改进的霍普金森压杆系统对25~800 ℃共9个温度等级的热处理试样分别进行3种弹速下的冲击压缩试验。试验结果表明：随着冲击速度的增加,25~700 ℃热处理试样的应力—应变曲线由“Ⅱ型”转变为“Ⅰ型”,而800 ℃热处理试样均表现出“Ⅰ型”应力—应变曲线特征。同一温度热处理下试块的峰值应力、应变和平均应变均随动荷载的升高而增大。相同的冲击速度下,300 ℃热处理试样的动力学性能有所改善,500 ℃后试样的动力学性能开始逐渐劣化。同一温度热处理试样的破碎程度随冲击速度的增加而增加;相同冲击速度下,热处理试样的破碎程度随温度的升高先减弱后增强。     

Effect of catalysts in the quality of syngas and by-products obtained by co-gasification of coal and wastes. 1. Tars and nitrogen compounds abatement

The aim of this work is to analyse the possibility of using co-gasification technology to process coal mixed with wastes to take profit of its energy content and at the same time to minimize the environmental impact associated with the use of wastes and to diminish the costs of flue gas treatment. The addition to coal of different types of materials, like: pine based waste, petcoke and polyethylene (PE), was not found to give rise to any operational problems, regarding both the feeding system and gasification process and led to higher energy conversions, however, the gas presented higher tars and hydrocarbons content. Several catalysts were tested, such as, dolomite, olivine, nickel and magnesium oxides, zinc oxides and cobalt and molybdenum oxides. Catalyst action was analysed in tars release and also in ammonia compounds reduction. The presence of catalysts allowed increasing hydrogen release, whilst there was a decrease in hydrocarbons and tars contents. A nickel-magnesium oxide was the catalyst that led to the highest reduction in hydrocarbons and tars. This catalyst also led to the lowest NH₃ content in the fuel gas produced, due to the catalyst efficiency in NH₃ destruction.     

An improved ν-twin support vector machine

Twin support vector machine (TSVM) is regarded as a milestone in the development of the powerful SVM. It finds two nonparallel planes by resolving a pair of smaller-sized quadratic programming problems rather than a single large one, which makes the learning speed of TSVM approximately four times faster than that of the standard SVM. However, the empirical risk minimization principle is implemented in the TSVM, so it easily leads to the over-fitting problem and reduces the prediction accuracy of the classifier. ν-TSVM, as a variant of TSVM, also implements the empirical risk minimization principle. To enhance the generalization ability of the classifier, we propose an improved ν-TSVM by introducing a regularization term into the objective function, so there are two parts in the objective function, one of which is to maximize the margin between the two parallel hyper-planes, and the other one is to minimize the training errors of two classes of samples. Therefore the structural risk minimization principle is implemented in our improved ν-TSVM. Numerical experiments on one artificial dataset and nine benchmark datasets show that our improved ν-TSVM yields better generalization performance than SVM, ν-SVM, and ν-TSVM. Moreover, numerical experiments with different proportions of outliers demonstrate that our improved ν-TSVM is robust and stable. Finally, we apply our improved ν-TSVM to two BCI competition datasets, and also obtain better prediction accuracy.     

基于条件随机场的低图像质量车牌字符分割

提出一种基于条件随机场的车牌字符分割算法,能够对光照不均、相机拍摄角度造成的低图像质量的车牌图像,特别是日益增多的车牌边框与字符相连接车牌图像进行有效的字符分割。算法首先进行车牌图像校正,然后利用标注车牌数据进行模型学习,对车牌图像像素列进行分类识别,最后组合成车牌字符分割结果。理论分析与实验结果验证了算法的有效性。     

炭黑填充硬聚氯乙烯的改性

为使聚氯乙烯具有抗静电性能,采用加入具有导电性填料的方法,但加入大量的填料,会使硬聚氯乙烯的冲击性能降低,加工性能变差。本文是在以炭黑为填料的基础上,研究不同的改性剂和加工助剂改进硬聚氯乙烯的效果,结果表明,加入冲击改性剂和加工助剂后,大大增加了硬聚氯乙烯的冲击强度,且加工性能也得到改善,同时由于炭黑具有补强效果,其拉伸强度和弯曲强度在加入改性剂后也能满足使用要求。     

基于幂图的属性约简

针对粗糙集理论中基于差别矩阵的属性约简方法存在的不足,提出一种基于幂图的属性约简算法.首先通过修改样本决策属性值将不相容决策表转化为简化的相容决策表;然后将样本对概念与幂图概念相结合,将基于修正差别矩阵的不相容决策表的属性约简转化为幂图的搜索问题;最后通过实例和实验验证了所提出算法的有效性.