{"title":"基于神经自适应控制的活性污泥生物反应器溶解氧控制","authors":"S. Mirghasemi, C. Macnab, A. Chu","doi":"10.1109/CICA.2014.7013237","DOIUrl":null,"url":null,"abstract":"In a mixed liquor biological wastewater treatment process, the dissolved oxygen level is a very important factor. This paper proposes an adaptive neural network control strategy to maintain a set point in aerated bioreactors. The proposed method prevents weight drift and associated bursting, without sacrificing performance. The controller is tested on a simplified version of the benchmark simulation model number 1, with disturbances in influent. The proposed controller outperforms PI control.","PeriodicalId":340740,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Control and Automation (CICA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Dissolved oxygen control of activated sludge biorectors using neural-adaptive control\",\"authors\":\"S. Mirghasemi, C. Macnab, A. Chu\",\"doi\":\"10.1109/CICA.2014.7013237\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In a mixed liquor biological wastewater treatment process, the dissolved oxygen level is a very important factor. This paper proposes an adaptive neural network control strategy to maintain a set point in aerated bioreactors. The proposed method prevents weight drift and associated bursting, without sacrificing performance. The controller is tested on a simplified version of the benchmark simulation model number 1, with disturbances in influent. The proposed controller outperforms PI control.\",\"PeriodicalId\":340740,\"journal\":{\"name\":\"2014 IEEE Symposium on Computational Intelligence in Control and Automation (CICA)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Symposium on Computational Intelligence in Control and Automation (CICA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CICA.2014.7013237\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Symposium on Computational Intelligence in Control and Automation (CICA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICA.2014.7013237","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dissolved oxygen control of activated sludge biorectors using neural-adaptive control
In a mixed liquor biological wastewater treatment process, the dissolved oxygen level is a very important factor. This paper proposes an adaptive neural network control strategy to maintain a set point in aerated bioreactors. The proposed method prevents weight drift and associated bursting, without sacrificing performance. The controller is tested on a simplified version of the benchmark simulation model number 1, with disturbances in influent. The proposed controller outperforms PI control.