文献类型：期刊文章

作　　者：曹柳林[1] 李晓光[1] 王晶[1]

机构地区：[1]北京化工大学信息科学与技术学院自动化研究所,北京100029

出　　处：《化工学报》

基　　金：国家自然科学基金项目(60704011)~~

年　　份：2008

卷　　号：59

期　　号：7

起止页码：1848-1853

语　　种：中文

收录情况：AJ、BDHX、BDHX2004、CAS、CSCD、CSCD2011_2012、EI(收录号：20083111424369)、IC、JST、RCCSE、SCOPUS、ZGKJHX、核心刊

摘　　要：A complex exothermic batch reactor model was developed by using structure approaching hybrid neural networks(SAHNN).The optimal reactor temperature profiles were obtained via the PSO-SQP algorithm solving maximum product concentration problem based on recurrent neural network(RNN).Considering model-plant mismatches and unmeasured disturbances,a novel extended integral square error index(EISE)was proposed,which introduced mismatches of model-plant into the optimal control profile.The approach used a feedback channel for the control and therefore dramatically enhanced the robustness and anti-disturbance performance.The stability analysis of the one-step-ahead control strategy through SAHNN-based model was described based on Lyapunov theory in detail.The result fully demonstrated the effectiveness of the proposed optimal control profile.

关 键 词：结构逼近式混合神经网络  间歇反应器 最优控制

分 类 号：TQ316.2]