LI Yan
,
MAO Zhi-zhong
,
WANG Yan
,
YUAN Ping
,
JIA Ming-xing
钢铁研究学报(英文版)
In electric arc furnace smelting, electrode regulator system is a key link. A good electrode control algorithm will reduce energy consumption effectively and shorten smelting time greatly. The offline design online synthesis model predictive control algorithm is proposed for electrode regulator system with input and output constraints. On the offline computation, the continuum of terminal constraint sets will be constructed. On the online synthesis, the time-varying terminal constraint sets will be adopted and at least one free control variable will be introduced to solve the min-max optimization control problem. Then Lyapunov method will be adopted to analyze closed-loop system stability. Simulation and field trial results show that the proposed offline design online synthesis model predictive control method is effective.
关键词:
electrode regulator system
,
model predictive control
,
time-varying terminal constraint set
,
Lyapunov stability
,
linear matrix inequalities (LMIs)
HE Haitao
,
LI Yan
钢铁研究学报(英文版)
In the traditional flatness pattern recognition neural network, the topologic configurations need to be rebuilt with a changing width of cold strip. Furthermore, the large learning assignment, slow convergence, and local minimum in the network are observed. Moreover, going by the structure of the traditional neural network, according to experience, the model is timeconsuming and complex. Thus, a new approach of flatness pattern recognition is proposed based on the CMAC (cerebellar model articulation controllers) neural network. The difference in fuzzy distances between samples and the basic patterns is introduced as the input of the CMAC network. Simultaneously, the adequate learning rate is improved in the error correction algorithm of this neural network. The new approach with advantages, such as high learning speed, good generalization, and easy implementation, is efficient and intelligent. The simulation results show that the speed and accuracy of the flatness pattern recognition model are obviously improved.
关键词:
flatness;pattern recognition;CMAC neural network;fuzzy distance
LI Yan
,
侯万国
应用化学
doi:10.3969/j.issn.1000-0518.2008.08.022
研究了阳离子淀粉(CS)/Mg-Al类水滑石(HTlc)悬浮体系的粘度行为.分别考察了pH值对CS水溶液粘度的影响,考察了Mg-AlHTlc与CS固体质量比值(R)及体系pH值对CS/Mg-Al-HTlc悬浮体粘度的影响.结果发现,CS水溶液在pH值为3～4时的粘度最大,强酸强碱条件下粘度急剧降低;当pH值为8.68～8.80时,CS/Mg-Al-HTlc悬浮体的粘度随Mg-Al-HTlc的加入(R值的增加)先增加后降低,出现一极值.随着R值的增大,CS/Mg-Al-HTlc体系出现最大粘度值所对应的pH值也增大.低pH值时,R值小的CS/Mg-Al-HTlc体系粘度最大;高pH值时,R值大的CS/Mg-Al-HTlc体系粘度最大.
关键词:
阳离子淀粉
,
Mg-Al类水滑石
,
流变性
,
粘度
ZHANG Rui-qian
,
LI Yan
,
WANG Xiao-min
钢铁研究学报(英文版)
The compatibility of the austenitic AISI 304 steel with Pb-Bi-Sn alloy was analyzed. The AISI 304 steels were immersed in stagnant molten Pb-33.3Bi-33.3Sn alloy at 400, 500 and 600 ℃ for different exposure times (100-2000 h) respectively. X-Ray diffraction spectrum (XRD) with a Y-4Q system (CuKα, λ=0.15478 nm) was used to identify the phases on the surface of specimens after exposing to Pb-Bi-Sn liquid metal (LM). The surface and cross section of the specimens were analyzed by means of scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDX). The result showed that a FeSn alloy layer on the surface of all specimens was formed, and it prevented AISI 304 steel matrix from penetration attack and loss of alloy elements at 400 and 500 ℃.
关键词:
austenitic steel
,
lead-bismuth-tin alloy
,
compatibility
,
liquid-metal bond
,
uranium-zirconium hydride fuel
