文献类型：期刊文献

英文题名：Intelligent control of a grain drying system using a GA-SVM-IMPC controller

作者：Dai, Aini[1,2];Zhou, Xiaoguang[1];Liu, Xiangdong[3];Liu, Jingyun[4];Zhang, Chi[1]

第一作者：Dai, Aini

通讯作者：Zhou, XG[1]

机构：[1]Beijing Univ Posts & Telecommun, Sch Automat, 10 Xitucheng Rd, Beijing 100876, Peoples R China;[2]Qingdao Agr Univ, Sci & Informat Coll, Qingdao, Peoples R China;[3]China Agr Univ, Coll Engn, Beijing, Peoples R China;[4]Beijing Union Univ, Sch Automat, Beijing, Peoples R China

第一机构：Beijing Univ Posts & Telecommun, Sch Automat, 10 Xitucheng Rd, Beijing 100876, Peoples R China

通讯机构：[1]corresponding author), Beijing Univ Posts & Telecommun, Sch Automat, 10 Xitucheng Rd, Beijing 100876, Peoples R China.

年份：2018

卷号：36

期号：12

起止页码：1413-1435

外文期刊名：DRYING TECHNOLOGY

收录：;EI(收录号：20180104603617);Scopus(收录号：2-s2.0-85039781441);WOS:【SCI-EXPANDED(收录号:WOS:000441236800003)】；

基金：The paper was in part supported by BUPT Excellent Ph.D. Students Foundation (CX2017405), in part supported by the China National Common Weal Industrial Special Scientific Research Funds for Grain Industry (201413006) and we also would like to thank the cooperation of research group and the experimental help of the engineers at Dongyu Machinery Co. Ltd., China.

语种：英文

外文关键词：Genetic algorithm; grain drying; IMC; mixed flow drying; SVM

摘要：The grain drying is difficult to control because of its characteristics of long delay, strong nonlinearity, and uncertainty parameters. The aim of the paper is to design a suitable controller for a newly designed grain dryer. First, a nonlinear math model of the wheat mixed flow drying was established and analyzed based on the fundamental laws of simultaneous heat and mass transfer. The simulations for the batch circulating drying process and the continuous grain drying process have been made and the simulation results show that it fits well with the actual drying process. Second, an internal model proportional integral derivative (PID) controller (IMPC) based on the support vector machine (SVM) algorithm and the genetic algorithm (GA-SVM-IMPC) was proposed from the view of the energy loss and the dried grain quality. The structure of the GA-SVM-IMPC controller consists of a SVM prediction model, a SVM inverse model controller, a PID controller and a genetic optimization algorithm. Finally, the effectiveness of this controller was demonstrated by computer simulations, and the comparative study with the other controllers further confirmed the superiority of the proposed dryer controller.