文献类型：会议论文

英文题名：Batch-to-batch control of batch processes based on multilayer recurrent fuzzy neural network

作者：Liu, He[1];Jia, Li;Liu, Qing[1];Huang, Dao[1]

机构：[1]E China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China

会议论文集：2007 International Conference on Intelligent Systems and Knowledge Engineering

会议日期：OCT 15-16, 2007

会议地点：Southwest Jiaotong Univ, Chengdu, PEOPLES R CHINA

主办单位：Southwest Jiaotong Univ

语种：英文

外文关键词：batch-to-batch control; iterative learning control; recurrent neural network; batch process

摘要：The batch-to-batch model-based iterative optimal control strategy for batch processes is realized based on multilayer recurrent fuzzy neural network (MRFNN) and chaotic search. MRFNNs are used to model batch processes. Modeling and optimization problems are mainly solved by chaotic search. Due to model-plant mismatches and disturbances, the calculated optimal control profile may not be optimal when applied to the actual process. Current predictions are improved by prediction errors from previous batches, and the model errors are gradually reduced from batch-to-batch. Furthermore, the control strategy is developed for temperature tracking control. The effectiveness is verified on simulated batch reactors.