{"title":"The application of GA-based PID parameter optimization for the control of superheated steam temperature","authors":"Wang Jingi, Xuejin Yang, Chen Lei","doi":"10.1109/ICMLC.2012.6359461","DOIUrl":null,"url":null,"abstract":"Aiming at the characteristics as time-delay, large inertia of superheated steam temperature in the power plants, an optimal PID controller which takes the overshoot, rise time and setting time of the system as the performance indicators have been proposed. The PID parameters were optimized by the means of the genetic algorithm with real number encoding. Finally, a group of optimal PID parameters were obtained. Simulation results indicate the GA-Based PID controller in this paper still has the ability of self-learning and adaptive even the controlled object is greatly changed. The controller can acquire an ideal control effect with shorter dynamic transition time, smaller overshoot and oscillation when the controlled object is changing.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2012.6359461","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Aiming at the characteristics as time-delay, large inertia of superheated steam temperature in the power plants, an optimal PID controller which takes the overshoot, rise time and setting time of the system as the performance indicators have been proposed. The PID parameters were optimized by the means of the genetic algorithm with real number encoding. Finally, a group of optimal PID parameters were obtained. Simulation results indicate the GA-Based PID controller in this paper still has the ability of self-learning and adaptive even the controlled object is greatly changed. The controller can acquire an ideal control effect with shorter dynamic transition time, smaller overshoot and oscillation when the controlled object is changing.