A fuzzy cerebellar model articulation controller based visual servo system for robot

This paper presents a novel online learning visual servo controller integrating the FCMAC with proportion controller for the control of position of manipulator end-effector. Since the FCMAC has good learning capability and fast learning speed, and can save much computer memory space by fuzzy processing of input space division and memory unit activation, it is used to develop an adaptive control law by learning the relationship between the image feature errors and manipulator input, and the aim of online learning of the FCMAC is to minimize the output of proportion controller. Furthermore, the FCMAC has no need for models of robot manipulator and image feature extraction, so that the capability of proposed controller for tasks under uncertain environment can be improved. Finally, the proposed controller is proved to be effective by the experiment, and compared with BP neural network.     

基于提高弱电网新能源并网水平的逆变器功率-电压控制策略

传统功率-电流控制的并网逆变器存在谐波振荡等交互稳定性问题,限制了新能源的并网水平,尤其在弱交流电网中更为突出.为克服上述缺点,提出了一种新型功率-电压控制策略.首先在旋转dq坐标系下建立了逆变器输出阻抗的动态模型,包括主电路参数,锁相环(PLL)动态参数和调节器参数;然后基于波特图分析传统功率-电流控制策略下和本文所提功率-电压控制策略下逆变器输出阻抗的频率特性,证明了本文所提功率-电压控制策略稳定性,可以减小PLL带宽和输出功率的影响,从而提高弱电网中逆变器的额定功率注入功率,最后仿真和实验结果验证了所提出控制策略的有效性.     

含高渗透率光伏的配电网就地-分布式电压控制

随着配电网中分布式光伏渗透率的逐步提高,发电功率和负荷需求不平衡导致的电压越限问题日益突出.为充分调用可控资源进行调压,同时降低系统的通信量和计算量,文中基于配电网节点的近似电压灵敏度,结合就地控制和分布式控制的特点,提出一种含高渗透率光伏的配电网电压控制策略.该策略利用本地量测数据和分布式通信信息,通过各关键节点的无功协调控制和有功优化调度,实现系统电压的经济快速控制.仿真结果表明,所提策略具有良好的电压控制效果和经济性,能够降低系统的运行成本.     

Facile synthesis of nitrogen and oxygen co-doped hierarchical porous carbon materials for high performance super capacitors

Journal of Porous Materials - Nitrogen and oxygen co-doped hierarchical porous carbons (NOPCs) is prepared by the pyrolysis of polyethylene glycol-200 (PEG) and triazine carbon forming agent (CFA)...     

Indium tin oxide nanosized composite powder prepared using waste ITO target

Indium tin oxide （ITO） nano-particles were prepared directly using waste ITO target, which had been coated by magnetron controlled sputtering. The waste ITO target was cleaned with de-ionized water, and then dissolved in acid, filtrated, neutralized, manipulated through azeotropic distillation and finally dried, and in this way the precursor of indium tin hydroxide was obtained. The nanosized rio composite powder was prepared after the precursor heat-treated at 500℃ for 2 h. TEM images show a narrow distribution of particle size is 5-20 nm and the particle size can be controlled. Its granule has a spherical shape and the dispersion of the particle is well. X-ray diffraction （XRD） patterns indicate the only cubic In2O3 phase in the ITO powder hot-treated at 500℃. The purity of ITO composite powder is 99.9907%. The content of radium within filtrate was detected by using the EDTA titration of determination of indium in the ITO powder and ITO target. Appropriate amount of SnCl4.5H2O was dissolved in the filtrate, and then ITO powder containing 10 wt.% SnO2 was successfully prepared by heat-treating.     

聚糖菌反硝化影响因素及内碳源转化特性

在SBR反应器中以乙酸钠为碳源、\mathrm{N}{\mathrm{O}}_3^{-}-N为电子受体成功富集了反硝化聚糖菌，并采用批次实验进一步考察了进水C/N比（3.3,6.7,10）、电子受体（\mathrm{N}{\mathrm{O}}_3^{-}-N、\mathrm{N}{\mathrm{O}}_2^{-}-N）、碳源类型（乙酸钠、葡萄糖）对反硝化聚糖菌活性的影响及内碳源转化特性。实验结果表明，进水C/N比越高，系统\mathrm{N}{\mathrm{O}}_x^{-}-N去除率越高，厌氧段合成PHB越多，但进水C/N比过高会导致普通反硝化菌占优势，影响内碳源反硝化效率，进水C/N比为6.7较为合适；以\mathrm{N}{\mathrm{O}}_3^{-}-N为电子受体长期培养的DGAOs系统未经\mathrm{N}{\mathrm{O}}_2^{-}-N驯化，对\mathrm{N}{\mathrm{O}}_2^{-}-N同样具有良好的反硝化性能，在投加与\mathrm{N}{\mathrm{O}}_3^{-}-N相同浓度的\mathrm{N}{\mathrm{O}}_2^{-}-N后，系统\mathrm{N}{\mathrm{O}}_x^{-}-N去除率达89.6%；当以葡萄糖为碳源时，DPAOs在厌氧段合成的PHB的量仅为以乙酸钠为碳源时合成PHB量的79.5%，且厌氧段葡萄糖利用率仅为72.8%，远远小于乙酸钠的利用率。     

中继协同无人机辅助的认知无线电网络安全通信

针对中继协同无人机（UAV）辅助的无线通信网络,提出一种基于认知无线电网络（CRN）的物理层安全通信方案。利用二次发射机协同解码转发中继向目的接收机发送机密消息,将UAV用作移动干扰器发送干扰噪声,以降低窃听者的解码能力。在不影响主用户通信的前提下,通过联合优化UAV的飞行轨迹和发射功率提高系统的平均保密率,采用基于连续凸逼近的算法求解近似凸规划的保密率最大化问题。仿真结果表明,相较于优化功率和优化轨迹这两种传统方案,该方案能够进一步提高CRN系统通信的安全性。     

人工肺-嗅觉系统集成与混合气体识别方法

针对仿人机器人的嗅觉及多种混合气体识别问题,提出一种人工肺-嗅觉系统(HALOS-I)及基于主动呼吸的气体识别方法.该系统硬件主要集成了微型真空泵、酒精/硫化氢/氨气/烟雾/甲烷5种气体传感器、单片机以及信号采集与处理电路;分别用K-均值聚类分析法、遗传算法结合神经网络(GA+BP)、三级级联神经网络(GA+3BP)进行了5种单一气体及4种混合气体的识别实验,结果表明:GA+BP算法仅对5种单一气体识别率达到90%以上,加入混合气体后识别率较低;GA+3BP算法除对硫化氢和烟雾的混合气体识别率为70%以外,对其余8种气体识别率均在90%以上,表明GA与多级级联BP神经网络相结合方法对多种单一及混合气体具有较高的识别率.     

采用水量平衡法分析呼伦湖水域面积变化因素

为摸清呼伦湖水位下降而导致周边生态环境恶化的原因,以呼伦湖为研究对象,通过Landsat ETM+和OLI影像资料得到呼伦湖面积变化情况,将1960-2013年共分为4个时期,利用水量平衡法分析影响呼伦湖水量的主要因素。结果表明:不同时期影响因素及影响程度均不同,径流量的R值分别为0.42、0.93、0.60、0.86,每个时期影响最大值,面积减小了213 km~2,水位降低了3.35m。综合以上所述,得出入湖河流的径流量为调控呼伦湖水量的主控因子,其水域面积的持续萎缩主要是受气候变化和人类活动影响。