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131.
This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes. 相似文献
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针对流体输送埋地管道泄漏问题,设计了一种利用管道机器人携带封堵气囊进行快速应急封堵修复的埋地管道泄漏内封堵装置。采用矩阵变换方法建立了牵引系统驱动轮过弯方程,利用MATLAB软件对过弯方程进行了验证,同时利用ADAMS软件仿真分析过弯路径与驱动轮转角对牵引系统行走速度的影响。研究结果表明:由两个串联封堵器组成的应急封堵系统可满足复杂工况下的管道泄漏封堵要求;牵引系统驱动轮在弯管内部行走时,单轮速度呈周期性变化,但三个驱动轮整体周期运动特性一致;驱动轮转角在25°~40°时,牵引系统行走速度与驱动轮转角成正比,且转角为30°时驱动效果最好。该内封堵装置的结构设计可为管道泄漏应急封堵领域装备的研发提供重要参考。 相似文献
134.
Ricardo Cambraia Parreira Diana Paola Gmez‐Mendoza Itamar Couto Guedes de Jesus Rafael Pereira Lemos Anderson Kennedy Santos Cristiana Perdigo Rezende Henrique Csar Pereira Figueiredo Mauro Cunha Xavier Pinto Frank Kjeldsen Silvia Guatimosim Rodrigo Ribeiro Resende Thiago Verano‐Braga 《Proteomics. Clinical applications》2020,14(4)
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Mani Balamurugan Hui‐Yun Jeong Venkata Surya Kumar Choutipalli Jung Sug Hong Hongmin Seo Natarajan Saravanan Jun Ho Jang Kang‐Gyu Lee Yoon Ho Lee Sang Won Im Venkatesan Subramanian Sun Hee Kim Ki Tae Nam 《Small (Weinheim an der Bergstrasse, Germany)》2020,16(25)
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. 相似文献
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Shuang Shao Yong Liu Chun-Shui Xu Ying-Xuan Xu Bin Wu Xiao-Shu Zeng Xian-Feng Lu Xiang-Jie Yang 《金属学报(英文版)》2015,(1):7-14
The microstructure and mechanical properties of Mg–6Zn–1Y and Mg–6Zn–3Y(wt%) alloys under different cooling rates were investigated. The results show that the second dendrite arm spacing(SDAS) of Mg–6Zn–1Y and Mg–6Zn–3Y is reduced by 32 and 30% with increasing cooling rates(Rc) from 10.2 to 23 K/s, which can be predicted using a empirical model of SDAS=68 R 0:45:45cand SDAS=73 R 0c, respectively. The compressive strength of both alloys increases with increasing the cooling rate, which is attributed to the increase of volume fraction(Vf) of secondary phases under high cooling rate. The interaction of the cooling rate and component with SDAS has been theoretically analyzed using interdependence theory. 相似文献