F. A. Thobiani, Esra Elhadad, A. Shamekh, A. Altowati
{"title":"遗传算法在半批量聚合温度控制中的应用","authors":"F. A. Thobiani, Esra Elhadad, A. Shamekh, A. Altowati","doi":"10.1109/i2cacis54679.2022.9815457","DOIUrl":null,"url":null,"abstract":"A Genetic Algorithm (GA) combined with a two-loop PID-PI control structure is utilized to control the temperature of a semi-batch polymerization reactor (SBPR). The Chylla-Haase benchmark model is considered in this work. The GA-based optimization is exploited in single and multi-objective problems to determine the desired controller setting. The study is conducted in the Matlab/Simulink environment with several simulation scenarios. The obtained results reveal that the GA-based PID-PI technique can provide consistent performance that satisfies the system constraints. Moreover, the proposed algorithm does not contain heavy calculation burdens and can be tuned offline.","PeriodicalId":332297,"journal":{"name":"2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of Genetic Algorithm in Semi-batch Polymerization Temperature Control\",\"authors\":\"F. A. Thobiani, Esra Elhadad, A. Shamekh, A. Altowati\",\"doi\":\"10.1109/i2cacis54679.2022.9815457\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Genetic Algorithm (GA) combined with a two-loop PID-PI control structure is utilized to control the temperature of a semi-batch polymerization reactor (SBPR). The Chylla-Haase benchmark model is considered in this work. The GA-based optimization is exploited in single and multi-objective problems to determine the desired controller setting. The study is conducted in the Matlab/Simulink environment with several simulation scenarios. The obtained results reveal that the GA-based PID-PI technique can provide consistent performance that satisfies the system constraints. Moreover, the proposed algorithm does not contain heavy calculation burdens and can be tuned offline.\",\"PeriodicalId\":332297,\"journal\":{\"name\":\"2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/i2cacis54679.2022.9815457\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/i2cacis54679.2022.9815457","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Genetic Algorithm in Semi-batch Polymerization Temperature Control
A Genetic Algorithm (GA) combined with a two-loop PID-PI control structure is utilized to control the temperature of a semi-batch polymerization reactor (SBPR). The Chylla-Haase benchmark model is considered in this work. The GA-based optimization is exploited in single and multi-objective problems to determine the desired controller setting. The study is conducted in the Matlab/Simulink environment with several simulation scenarios. The obtained results reveal that the GA-based PID-PI technique can provide consistent performance that satisfies the system constraints. Moreover, the proposed algorithm does not contain heavy calculation burdens and can be tuned offline.