{"title":"基于粒子群算法的污水管网最优流量控制研究","authors":"Lihui Cen, Y. Xi","doi":"10.1109/ISIC.2007.4450895","DOIUrl":null,"url":null,"abstract":"Considering the flow control of large-scale sewer networks to minimize overflows, a control algorithm based on particle swarm optimization with mutation operator (MPSO) is proposed in this paper to achieve optimal operations of reservoir gates. By introducing element models, the mathematical model of whole sewer network can be formulated. The algorithm is applied to solve the optimization problem and generate control actions. To avoid the algorithm being trapped into local optimum, a mutation operator is introduced at the last stage of evolution, which guarantees the optimal solution. The optimal solution obtained by evolution is a sequence of gate opening heights, offering a direction to adjust the gates step by step. The effects under different external inflow scenarios and gate settings are investigated in the test case. The significant improvement in overflow reduction demonstrates its efficiency.","PeriodicalId":184867,"journal":{"name":"2007 IEEE 22nd International Symposium on Intelligent Control","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Particle Swarm Optimization for Optimal Flow Control in Combined Sewer Networks-A Case Study\",\"authors\":\"Lihui Cen, Y. Xi\",\"doi\":\"10.1109/ISIC.2007.4450895\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Considering the flow control of large-scale sewer networks to minimize overflows, a control algorithm based on particle swarm optimization with mutation operator (MPSO) is proposed in this paper to achieve optimal operations of reservoir gates. By introducing element models, the mathematical model of whole sewer network can be formulated. The algorithm is applied to solve the optimization problem and generate control actions. To avoid the algorithm being trapped into local optimum, a mutation operator is introduced at the last stage of evolution, which guarantees the optimal solution. The optimal solution obtained by evolution is a sequence of gate opening heights, offering a direction to adjust the gates step by step. The effects under different external inflow scenarios and gate settings are investigated in the test case. The significant improvement in overflow reduction demonstrates its efficiency.\",\"PeriodicalId\":184867,\"journal\":{\"name\":\"2007 IEEE 22nd International Symposium on Intelligent Control\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 IEEE 22nd International Symposium on Intelligent Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIC.2007.4450895\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE 22nd International Symposium on Intelligent Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIC.2007.4450895","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Particle Swarm Optimization for Optimal Flow Control in Combined Sewer Networks-A Case Study
Considering the flow control of large-scale sewer networks to minimize overflows, a control algorithm based on particle swarm optimization with mutation operator (MPSO) is proposed in this paper to achieve optimal operations of reservoir gates. By introducing element models, the mathematical model of whole sewer network can be formulated. The algorithm is applied to solve the optimization problem and generate control actions. To avoid the algorithm being trapped into local optimum, a mutation operator is introduced at the last stage of evolution, which guarantees the optimal solution. The optimal solution obtained by evolution is a sequence of gate opening heights, offering a direction to adjust the gates step by step. The effects under different external inflow scenarios and gate settings are investigated in the test case. The significant improvement in overflow reduction demonstrates its efficiency.