{"title":"球磨机制粉系统的自整定多变量PID解耦控制","authors":"Jie-sheng Wang","doi":"10.1109/ICNC.2007.655","DOIUrl":null,"url":null,"abstract":"Ball mill coal pulverizing system of pelletizing plant is a complex nonlinear multivariable process with strongly coupling and time-delay, whose operations often varies violently. The automatic control of such systems is a research focus in the process control area. A new multivariable PID decoupling controller is proposed in this paper, which consists of diagonally matrix method-based decomposition compensatory unit, PID controller and fuzzy self-tuning components unit with scaling facto. Particle swarm optimization algorithm is also adopted to optimize parameters of PID controller. Simulation results show the validity of the model obtained and the control method proposed in this paper, the new method can overcome nonlinear and strong coupling features of the system in a wide range, and it has strong robustness and adaptability.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Self-Tuning Multivariable PID Decoupling Controller of Ball Mill Pulverizing System\",\"authors\":\"Jie-sheng Wang\",\"doi\":\"10.1109/ICNC.2007.655\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ball mill coal pulverizing system of pelletizing plant is a complex nonlinear multivariable process with strongly coupling and time-delay, whose operations often varies violently. The automatic control of such systems is a research focus in the process control area. A new multivariable PID decoupling controller is proposed in this paper, which consists of diagonally matrix method-based decomposition compensatory unit, PID controller and fuzzy self-tuning components unit with scaling facto. Particle swarm optimization algorithm is also adopted to optimize parameters of PID controller. Simulation results show the validity of the model obtained and the control method proposed in this paper, the new method can overcome nonlinear and strong coupling features of the system in a wide range, and it has strong robustness and adaptability.\",\"PeriodicalId\":250881,\"journal\":{\"name\":\"Third International Conference on Natural Computation (ICNC 2007)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Third International Conference on Natural Computation (ICNC 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2007.655\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third International Conference on Natural Computation (ICNC 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2007.655","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Self-Tuning Multivariable PID Decoupling Controller of Ball Mill Pulverizing System
Ball mill coal pulverizing system of pelletizing plant is a complex nonlinear multivariable process with strongly coupling and time-delay, whose operations often varies violently. The automatic control of such systems is a research focus in the process control area. A new multivariable PID decoupling controller is proposed in this paper, which consists of diagonally matrix method-based decomposition compensatory unit, PID controller and fuzzy self-tuning components unit with scaling facto. Particle swarm optimization algorithm is also adopted to optimize parameters of PID controller. Simulation results show the validity of the model obtained and the control method proposed in this paper, the new method can overcome nonlinear and strong coupling features of the system in a wide range, and it has strong robustness and adaptability.