混合H2/H∞鲁棒控制器设计

在状态空间描述下,定义了混合H₂/H_∞控制的完整信息、完整控制、干扰顺馈、输出估计这4种典型情况.在二次稳定意义上,讨论了混合H₂/H_∞的性能指标,及这4种典型情况的混合H₂/H_∞线性反馈控制器设计,给出了充分必要条件.在典型情况分析的基础上,研究一般意义上的混合H₂/H_∞反馈控制器设计.H₂和H_∞的干扰输入阵及性能评价函数各不相同时的混合H₂/H_∞反馈控制器,与H₂和H_∞控制器设计相似,归结为解两个Riccati方程.但这两个Riccati方程含有参数,最优解要通过搜索这两个参数得到.结果包含了单纯的H₂和H_∞设计,可看作是H₂,H_∞和混合H₂/H_∞的统一设计方法.最后通过一个简单的例子,说明了控制器设计方法的可行性.     

基于模糊时序和支持向量机的高速公路SO2浓度预测算法

针对现有SO₂浓度预测方法中存在的污染物来源和影响因素认识不统一、小样本数据敏感、易于陷入局部最优等问题,文中提出了基于模糊时序和支持向量机的高速公路SO₂浓度预测算法,为搭建高速公路环境健康监测系统提供了可靠的理论支持.该方法依据SO₂浓度的季节变动规律,以季节作为时间序列,以24h为粒化窗宽,通过高斯核函数提取原始样本数据的特征值,输入支持向量机训练模型,并利用k重交叉验证法结合网格划分优化模型参数.文中应用该方法建立了SO₂浓度预测模型,并以2014年4月至2015年3月山西省太旧高速公路某监测点SO₂小时浓度监测值为样本数据,在MATLAB平台下应用LIBSVM工具实现了计算过程.结果表明,基于模糊时序和支持向量机的高速公路SO₂浓度预测算法不受机理性理论研究的限制,支持小样本学习,非线性拟合效果好,泛化能力强.     

MIMO离散时间系统混合l1/H2控制

研究了MIMO(多输入多输出)离散时间系统的混合l₁/H₂优化问题,该问题可描述为最优化一个传递函数矩阵的l₁范数同时保证另一个传递函数矩阵的H₂范数满足预定的指标.研究了最优目标函数值关于H₂范数指标的连续性.证明了MIMO系统混合l₁/H₂控制问题最优解的存在性.由于基于标定-Q(scaled-Q)方法求解MIMO混合l₁/H₂问题,避免了进行零点插值运算的困难.通过求解有限维非线性规划问题可得到最优目标值的收敛的上下界.     

基于博弈论的H2/H∞混合控制及其在汽车主动悬架中的应用

文章提出把H₂/H_∞混合控制问题抽象为两个对局者信息不完全情况下的非零和博弈模型.在构造2×2非零和博弈模型中把反映系统鲁棒性能通道和动态性能通道作为参加博弈的两方,以H_∞和H₂控制方案作为两种纯策略,基于纳什谈判解原理设计出求解H₂/H_∞混合控制问题纳什均衡点的一般算法.把该算法应用于汽车主动悬架设计出基于纳什均衡点的H₂/H_∞输出反馈控制器.使用MATLAB进行仿真,仿真结果表明主动悬架系统在保持鲁棒稳定性与获得优化的动态性能指标之间取得平衡.     

混合H2/H∞参数辨识

研究了混合H₂/H_∞参数辨识问题.将混合H₂/H_∞估计方法应用到系统参数辨识中,给出了混合H₂/H_∞参数辨识算法.所得的算法不仅能满足规定的鲁棒性能,且为最小二乘(LS)参数估计误差判据提供了一个最优上界.结果表明:提高辨识的鲁棒性,需要牺牲辨识的精度作为代价.最后,仿真结果也验证了该方法的有效性.     

基于最大相关熵准则的2维主成分分析

目的 本文针对基于最小均方差准则的主成分分析算法(如2DPCA-L₂(two-dimensional PCA with L₂-norm)算法和2DPCA-L₁(two-dimensional PCA with L₁-norm)算法)对外点敏感、识别率低的问题,结合信息论中的最大相关熵准则,提出了一种基于最大相关熵准则的2DPCA(2DPCA-MCC)。方法 2DPCA-MCC算法采用最大相关熵表示目标函数,通过半二次优化技术解决相关熵问题,降低了外点在目标函数评价中的贡献,从而提高了算法的鲁棒性和识别精度。结果 通过对比2DPCA-MCC算法和2DPCA-L₂、2DPCA-L₁在ORL人脸数据库上的识别效果,表明了2DPCA-MCC算法的识别率比2维主成分分析算法的识别率最低提高了近10%,最高提高了近30%。结论 提出了一种基于最大相关熵的2DPCA算法,通过半二次优化技术解决非线性优化问题,实验结果表明,本算法能够较好地解决外点问题,显著提高识别精度,适用于解决人脸识别中的外点问题。     

H2/H∞保性能控制理论在静止无功发生器控制中的应用

利用H₂/H_∞保性能控制理论和直接反馈线性化, 给出了单机无穷大系统中, 具有参数摄动的静止无功发生器(STATCOM)的非线性控制模型. 使用MATLAB软件得出H₂/H_∞保性能控制律, 表示为线性矩阵不等式(LMI).在扰动及参数摄动的条件下进行了仿真. 结果表明这种控制方法同时具有鲁棒性和最优性能, 降低了单纯H_∞控制方法的保守性, 提高了电力系统的稳定性, 并满足电压精度的要求.     

主动悬架H2/ 广义H2输出反馈控制

本文提出了一种主动悬架控制的H₂ /广义H₂ 输出反馈控制方法. 依照国际标准ISO2631.3选择垂直和俯仰加速度的频率加权. 根据路面干扰谱特征, 选用H₂ 范数作为乘坐舒适性的指标, 广义H₂ 范数描述轮胎接地性等时域约束要求. 在多目标控制框架下, 将输出反馈控制器的设计转化为求解LMI优化问题. 基于半车模型, 给出了输出反馈主动悬架系统的频域分析和时域仿真.     

GA-ELM在硫铁矿制酸尾气SO2浓度预测的应用

基于对整个生产流程的管控,使硫铁矿生产硫酸尾气的SO₂浓度达标排放,提出运用GA-ELM对制酸尾气SO₂浓度进行建模预测.在硫铁矿制酸的生产过程中采集对尾气SO₂浓度影响较大的关键点参数,运用GA-ELM神经网络对烟气制酸尾气SO₂浓度进行预测.该方法在某厂实际检验,其预测结果与实际数据吻合度较高,对于调整和优化工艺指标和尾气达标排放起到很好的指导作用.     

Multi-log2N交换网络的性能分析模型及控制算法

高速多平面交换网络解决了其内部冲突问题,但需要相应的路由控制算法的辅助,否则,内部冲突不能彻底解决.这是因为包在输入级路由平面的选择不够恰当,容易导致路由冲突的产生.因此,根据冲突链路集的思想,给出一种Multi-log₂N交换网络的控制算法.该算法控制分组在路由平面间的选择,不仅能够适用于RNB和SNB,还能实现单播和多播的控制,保障Multi-log₂N完全实现无阻塞.另一方面,Multi-log₂N消除了内部的链路冲突,提高了交换速率,但对其交换性能缺乏系统的理论分析.给出一种基于嵌入式马尔可夫链的分析模型,对Multi-log₂N网络中队列的使用及分组在队列中的平均等待时间、平均队长等相关性能指标进行了系统的分析,为基于Multi-log₂N的光交换节点的设计提供了良好的理论依据.     

基于TDLAS的二氧化碳检测技术综述

精确检测CO_(2)气体浓度、控制CO_(2)气体排放是治理大气温室效应过程中最重要的部分。可调谐半导体激光吸收光谱(TDLAS)因具有高灵敏度和高可靠性的特点,广泛应用于在线监测、微量气体检测等方面。分析了TDLAS测量气体浓度的基本原理,重点介绍了直接吸收法和波长调制法并比较了两种方法的优缺点,随后介绍了近几十年来国内外应用TDLAS技术在气体检测方面取得的研究进展。最后总结了基于TDLAS的二氧化碳气体检测技术,并对其未来应用进行了展望。     

Thin-film calorimetric H2O2 gas sensor for the validation of germicidal effectivity in aseptic filling processes

In common aseptic filling processes, hydrogen peroxide vapour is a predominantly applied antimicrobial for the inactivation of microorganisms in packages. During this process, the germicidal effectivity of the antimicrobial treatment depends especially on the H₂O₂ concentration of the gas mixture. For the detection of H₂O₂ in aseptic filling processes, a novel thin-film calorimetric gas sensor based on a differential set-up of a catalytically activated and a passivated temperature sensing element has been realised in the present work. The sensor device contains two meander-shaped platinum resistances as temperature sensing elements; both have been passivated with spin-coated perfluoralkoxy. As catalytically active materials for the calorimetric gas sensor, palladium, platinum black and manganese oxide particles have been studied in the developed experimental set-up, wherein MnO₂ has shown the highest sensitivity of 0.57 °C/% (v/v) towards H₂O₂. Afterwards, the characteristic of the sensor device with MnO₂ particles as catalyst has been examined at various H₂O₂ concentrations and additionally, the influence of gas temperature and gas flow rate on the sensor signal has been validated in the experimental set-up.     

Development of SAW-based multi-gas sensor for simultaneous detection of CO2 and NO2

A 440 MHz wireless and passive surface acoustic wave (SAW)-based multi-gas sensor integrated with a temperature sensor was developed on a 41° YX LiNbO₃ piezoelectric substrate for the simultaneous detection of CO₂, NO₂, and temperature. The developed sensor was composed of a SAW reflective delay lines structured by an interdigital transducer (IDT), ten reflectors, a CO₂ sensitive film (Teflon AF 2400), and a NO₂ sensitive film (indium tin oxide). Teflon AF 2400 was used for the CO₂ sensitive film because it provides a high CO₂ solubility, with good permeability and selectivity. For the NO₂ sensitive film, indium tin oxide (ITO) was used. Coupling of mode (COM) modeling was conducted to determine the optimal device parameters prior to fabrication. Using the parameters determined by the simulation results, the device was fabricated and then wirelessly measured using a network analyzer. The measured reflective coefficient S₁₁ in the time domain showed high signal/noise (S/N) ratio, small signal attenuation, and few spurious peaks. The time positions of the reflection peaks were well matched with the predicted values from the simulation. High sensitivity and selectivity were observed at each target gas testing. The obtained sensitivity was 2.12°/ppm for CO₂ and 51.5°/ppm for NO₂, respectively. With the integrated temperature sensor, temperature compensation was also performed during gas sensitivity evaluation process.     

Temperature dependent H2S and Cl2 sensing selectivity of Cr2O3 thin films

The conductometric gas sensing characteristics of Cr₂O₃ thin films - prepared by electron-beam deposition of Cr films on quartz substrate followed by oxygen annealing - have been investigated for a host of gases (CH₄, CO, NO₂, Cl₂, NH₃ and H₂S) as a function of operating temperature (between 30 and 300 °C) and gas concentration (1-30 ppm). We demonstrate that these films are highly selective to H₂S at an operating temperature of 100 °C, while at 220 °C the films become selective to Cl₂. This result has been explained on the basis of depletion of chemisorbed oxygen from the surface of films due to temperature and/or interaction with Cl₂/H₂S, which is supported experimentally by carrying out the work function measurements using Kelvin probe method. The temperature dependent selectivity of Cr₂O₃ thin films provides a flexibility to use same film for the sensing of Cl₂ as well as H₂S.     

Epitaxially grown graphene based gas sensors for ultra sensitive NO2 detection

Epitaxially grown single layer and multi layer graphene on SiC devices were fabricated and compared for response towards NO₂. Due to electron donation from SiC, single layer graphene is n-type with a very low carrier concentration. The choice of substrate is demonstrated to enable tailoring of the electronic properties of graphene, with a SiC substrate realising simple resistive devices tuned for extremely sensitive NO₂ detection. The gas exposed uppermost layer of the multi layer device is screened from the SiC by the intermediate layers leading to a p-type nature with a higher concentration of charge carriers and therefore, a lower gas response. The single layer graphene device is thought to undergo an n-p transition upon exposure to increasing concentrations of NO₂ indicated by a change in response direction. This transition is likely to be due to the transfer of electrons to NO₂ making holes the majority carriers.     

Improved crystalline structure and H2S sensing performance of CuO-Au-SnO2 thin film using SiO2 additive concentration

In situ SiO₂-doped SnO₂ thin films were successfully prepared by liquid phase deposition. The influence of SiO₂ additive as an inhibitor on the surface morphology and the grain size for the thin film has been investigated. These results show that the morphology of SnO₂ film changes significantly by increasing the concentration of H₂SiF₆ solution which decreases the grain size of SnO₂. The stoichiometric analysis of Si content in the SnO₂ film prepared from various Si/Sn molar ratios has also been estimated. For the sensing performance of H₂S gas, the SiO₂-doped Cu-Au-SnO₂ sensor presents better sensitivity to H₂S gas compared with Cu-Au-SnO₂ sensor due to the fact that the distribution of SiO₂ particles in grain boundaries of nano-crystallines SnO₂ inhibited the grain growth (<6 nm) and formed a porous film. By increasing the Si/Sn molar ratio, the SiO₂-doped Cu-Au-SnO₂ gas sensors (Si/Sn = 0.5) exhibit a good sensitivity (S = 67), a short response time (t_90% < 3 s) and a good gas concentration characteristic (α = 0.6074). Consequently, the improvement of the nano-crystalline structures and high sensitivity for sensing films can be achieved by introducing SiO₂ additive into the SnO₂ film prepared by LPD method.     

SnO2 thin film sensor with enhanced response for NO2 gas at lower temperatures

Semiconducting SnO₂ thin films having higher value of electrical conductivity have been deposited using RF sputtering technique in the reactive gas environment (30% O₂ + 70% Ar) using a metallic tin (Sn) target for detection of oxidizing NO₂ gas. The effect of growth pressure (12-18 mTorr) on the surface morphology and structural property of SnO₂ film was studied using Atomic force microscopy (AFM), Scanning electron microscopy (SEM) and X-ray Diffraction (XRD) respectively. Film deposited at 16 mTorr sputtering pressure was porous with rough microstructure and exhibits high sensor response (∼2.9 × 10⁴) towards 50 ppm NO₂ gas at a comparatively low operating temperature (∼100 °C). The sensor response was found to increase linearly from 1.31 × 10² to 2.9 × 10⁴ while the response time decrease from 12.4 to 1.6 min with increase in the concentration of NO₂ gas from 1 to 50 ppm. The reaction kinetics of target NO₂ gas on the surface of SnO₂ thin film at the Sn sites play important role in enhancing the response characteristics at lower operating temperature (∼100 °C). The results obtained in the present study are encouraging for realization of SnO₂ thin film based sensor for efficient detection of NO₂ gas with low power consumption.     

Unsupervised system to classify SO2 pollutant concentrations in Salamanca, Mexico

Salamanca is cataloged as one of the most polluted cities in Mexico. In order to observe the behavior and clarify the influence of wind parameters on the Sulphur Dioxide (SO₂) concentrations a Self-Organizing Maps (SOM) Neural Network have been implemented at three monitoring locations for the period from January 1 to December 31, 2006. The maximum and minimum daily values of SO₂ concentrations measured during the year of 2006 were correlated with the wind parameters of the same period. The main advantages of the SOM Neural Network is that it allows to integrate data from different sensors and provide readily interpretation results. Especially, it is powerful mapping and classification tool, which others information in an easier way and facilitates the task of establishing an order of priority between the distinguished groups of concentrations depending on their need for further research or remediation actions in subsequent management steps. For each monitoring location, SOM classifications were evaluated with respect to pollution levels established by Health Authorities. The classification system can help to establish a better air quality monitoring methodology that is essential for assessing the effectiveness of imposed pollution controls, strategies, and facilitate the pollutants reduction.     

Synthesis and enhanced gas sensing properties of crystalline CeO2/TiO2 core/shell nanorods

Crystalline CeO₂/TiO₂ core/shell nanorods were fabricated by a hydrothermal method and a subsequent annealing process under the hydrogen and air atmosphere. The thickness of the outer shell composed of crystal TiO₂ nanoparticles can be tuned in the range of 5-11 nm. The crystal core/shell nanorods exhibited enhanced gas-sensing properties to ethanol vapor in terms of sensor response and selectivity. The calculated sensor response based on the change of the heterojunction barrier formed at the interface between CeO₂ and TiO₂ is agreed with the experimental results, and thus the change of the heterojunction barrier at different gas atmosphere can be used to explain the enhanced ethanol sensing properties.     

Fabrication of N-type Fe2O3 and P-type LaFeO3 nanobelts by electrospinning and determination of gas-sensing properties

N-type Fe₂O₃ nanobelts and P-type LaFeO₃ nanobelts were prepared by electrospinning. The structure and micro-morphology of the materials were characterized by X-ray diffraction (XRD) and scanning of electron microscopy (SEM). The gas sensing properties of the materials were investigated. The results show that the optimum operating temperature of the gas sensors fabricated from Fe₂O₃ nanobelts is 285 °C, whereas that from LaFeO₃ nanobelts is 170 °C. Under optimum operating temperatures at 500 ppm ethanol, the response of the gas sensors based on these two materials is 4.9 and 8.9, respectively. The response of LaFeO₃-based gas sensors behaves linearly with the ethanol concentration at 10-200 ppm. Sensitivities to different gases were examined, and the results show that LaFeO₃ nanobelts exhibit good selectivity to ethanol, making them promising candidates as practical detectors of ethanol.