基金项目:国家自然科学青年基金(51605321);山西省自然科学基金(201701D221144)收稿日期:2021-05-07修回日期:2021-05-15第40卷第2期计算机仿真2023年2月文章编号:1006-9348(2023)02-0094-08基于AGA-Smith预估补偿PID的脱硝系统控制孟宏君1,王尚尚2,张凯奇1,李丽锋3(1.山西大学自动化与软件学院,山西太原030013;2.山西大学数学科学学院,山西太原030006;3.山西河坡发电有限责任公司,山西阳泉045011)摘要:为解决SNCR脱硝系统模型精度不高及脱硝控制效果不佳的现状,采集现场运行数据并预处理,利用IPSO算法分别辨识出系统在典型工况170MW和260MW下尿素溶液流量到NOx排放浓度过程的传递函数模型,辨识输出与原始输出的均方根误差值分别为3.13×10-2、7.11×10-2。在电站现场原有单回路PID控制策略基础上,将AGA-Smith预估补偿控制策略引入。仿真结果表明,在两种典型工况下,AGA-Smith预估补偿控制超调量更小,抵抗外来扰动的能力更强,且模型适配能力强于单回路PID控制,为电站现场SNCR脱硝控制提供了良好的技术参考。关键词:脱硝;模型辨识;预估补偿中图分类号:TP391.9文献标识码:BDenitrationSystemControlBasedonAGA-SmithPredictiveCompensationPIDMENGHong-jun1,WANGShang-shang2,ZHANGKai-qi1,LILi-feng3(1.CollegeofAutomationandSoftware,ShanxiUniversity,TaiyuanShanxi030013,China;2.CollegeofMathematicalSciences,ShanxiUniversity,TaiyuanShanxi030006,China;3.ShanxiHepoPowerGenerationCo.,Ltd.,YangquanShanxi045011,China)ABSTRACT:InordertosolvethecurrentsituationofpoormodelaccuracyanddenitrificationcontroleffectofSNCRdenitrificationsystem,fieldoperationdatawerecollectedandpre-processedtoidentifytheprocesstransferfunctionmodelfromureasolutionflowtoNOxemissionconcentrationundertypicaloperatingconditionsof170MWand260MWbyIPSOalgorithm,andtherootmeansquareerrorbetweentheidentificationoutputandtheoriginaloutputare3.13×10-2and7.11×10-2,respectively.Basedontheoriginalsingle-loopPIDcontrolstrategyinthepowerplantsite,theAGA-Smithpredictivecompensationcontrolwasintroduced.ThesimulationresultsshowthattheAGA-Smithpredictioncompensationcontrolhaslessovershootandbetterresistancetoexternaldisturbancesunderthetwotypica...