{"title":"Research on resonant power supply for plasma cleaning based on adaptive genetic optimization PID","authors":"Xue Jiaxiang, Wang Yitong, Ding Duhan, Zhou Gang","doi":"10.1109/IHMSC55436.2022.00015","DOIUrl":null,"url":null,"abstract":"In view of the large disturbance and non-linearity of the existing plasma discharge power supply system, an adaptive genetic optimization PID control algorithm is proposed to replace the original PID control algorithm. According to the three indexes of overshoot, regulation time and steady-state accuracy, the evaluation function is formulated. Considering the convergence performance and operation speed of the system, the dynamic crossover and mutation probabilities are formulated. Finally, the simulation program is built and the step response curves of the closed-loop transfer function before and after optimization are compared. The results show that the overshoot of the system decreases from 7.14% to 1.55%, and the regulation time decreases from 337.7μs to 5.17μs.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"56 7","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC55436.2022.00015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In view of the large disturbance and non-linearity of the existing plasma discharge power supply system, an adaptive genetic optimization PID control algorithm is proposed to replace the original PID control algorithm. According to the three indexes of overshoot, regulation time and steady-state accuracy, the evaluation function is formulated. Considering the convergence performance and operation speed of the system, the dynamic crossover and mutation probabilities are formulated. Finally, the simulation program is built and the step response curves of the closed-loop transfer function before and after optimization are compared. The results show that the overshoot of the system decreases from 7.14% to 1.55%, and the regulation time decreases from 337.7μs to 5.17μs.