Adaptive backstepping repetitive learning control design for nonlinear discrete‐time systems with periodic uncertainties

This paper addresses a tracking problem for uncertain nonlinear discrete‐time systems in which the uncertainties, including parametric uncertainty and external disturbance, are periodic with known periodicity. Repetitive learning control (RLC) is an effective tool to deal with periodic unknown components. By using the backstepping procedures, an adaptive RLC law with periodic parameter estimation is designed. The overparameterization problem is overcome by postponing the parameter estimation to the last backstepping step, which could not be easily solved in robust adaptive control. It is shown that the proposed adaptive RLC law without overparameterization can guarantee the perfect tracking and boundedness of the states of the whole closed‐loop systems in presence of periodic uncertainties. In addition, the effectiveness of the developed controller is demonstrated by an implementation example on a single‐link flexible‐joint robot. Copyright © 2014 John Wiley & Sons, Ltd.     

Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

介孔-大孔结构无定形硅-铝催化剂的核磁共振研究

合成了具有介孔-大孔双模型分级结构的无定形硅-铝催化剂,利用硅和铝核的固体魔角核磁共振谱,考察了合成样品中硅和铝结构上的原子特征.     

随机减量技术中周期激励的影响及消除方法

本文针对机械系统中通常存在确定性周期激励的事实 ,论证了周期干扰成分的存在对提取的随机减量特征信号的影响 ,基于数字滤波技术提出了一种从周期干扰环境中提取随机减量特征信号的简便方法。在回转机械稳定性监测中的应用实例表明本文提出的方法是有效的。     

草酸钙在硫酸软骨素自组装膜上周期沉淀的研究

利用硫酸软骨素(chondroitin sulfate，CS)在云母基底上通过浇铸法制备的自组装膜为基底，诱导草酸钙在其上的凝集生长。发现当硫酸软骨素的浓度为1．Omg／ml时在该膜体系中可形成规整的周期性草酸钙环状沉淀。这种有序的环状结构可能是耗散结构的一种具体表现形式。利用原子力显微镜(atomic forcemicroscope，AFM)和傅立叶红外光谱仪对这种结构进行了表征，实验结果显示合适浓度下形成的CS膜在一定程度上可以抑制草酸钙的凝集结晶，表明高分子基质与无机离子间强烈的相互作用对无机盐的成核结晶有显著影响，为探讨结石的形成与抑制提供了一定的实验依据。     

射频板条CO_2激光器并联谐振技术的研究

本文利用周期性网络模型计算了射频板条CO2激光器电极的纵向电压分布．探讨了并联谐振技术在板条器件中获得成功运用的原因．提出了利用并联谐振技术进一步提高电压分布均匀性的两个途径．     

New Reaction Engineering Concepts for Selective Oxidation Reactions

In order to enhance product yields in selective oxidation reactions, numerous reaction engineering concepts are being studied worldwide. Periodic operation has been investigated for decades, yet its application is limited to a few examples, such as the butane oxidation after DuPont or reverse-flow reactors for VOC removal. The use of microchannel reactors is a younger field, but it has already yielded promising results for process optimization. Catalytic wall reactors have proved to be a helpful tool for kinetic studies. On the laboratory scale, membrane reactors have displayed favorable behavior in selective oxidation. The Na vapor-catalyzed dehydrogenation of methanol to formaldehyde is a final example of an unusual new concept for selective oxidation.