{"title":"直升机比例模型参数优化的PI-D控制器","authors":"M. Khaldi, Tammam M. Obeid","doi":"10.1109/ICMET.2010.5598330","DOIUrl":null,"url":null,"abstract":"Scaled-model helicopters are highly nonlinear, coupled, and unstable machines. They have fast response and controlling them is very complicated and need high degree of precision. In this paper, a detailed nonlinear model is derived. The derived nonlinear model is linearized around a nominal point in the hovering state and a linear classical controller is designed. Then, an optimization algorithm is applied where the linear controller's parameters are adjusted offline so that the Integral Time-multiplied Square Error (ITSE), the error between the output response of the nonlinear system and the reference signal, is minimal. Both the linear and the optimized controllers are augmented with the nonlinear model and the simulation results are compared.","PeriodicalId":415118,"journal":{"name":"2010 International Conference on Mechanical and Electrical Technology","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"PI-D controller with optimized parameters of a scaled-model helicopter\",\"authors\":\"M. Khaldi, Tammam M. Obeid\",\"doi\":\"10.1109/ICMET.2010.5598330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Scaled-model helicopters are highly nonlinear, coupled, and unstable machines. They have fast response and controlling them is very complicated and need high degree of precision. In this paper, a detailed nonlinear model is derived. The derived nonlinear model is linearized around a nominal point in the hovering state and a linear classical controller is designed. Then, an optimization algorithm is applied where the linear controller's parameters are adjusted offline so that the Integral Time-multiplied Square Error (ITSE), the error between the output response of the nonlinear system and the reference signal, is minimal. Both the linear and the optimized controllers are augmented with the nonlinear model and the simulation results are compared.\",\"PeriodicalId\":415118,\"journal\":{\"name\":\"2010 International Conference on Mechanical and Electrical Technology\",\"volume\":\"118 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Mechanical and Electrical Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMET.2010.5598330\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Mechanical and Electrical Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMET.2010.5598330","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PI-D controller with optimized parameters of a scaled-model helicopter
Scaled-model helicopters are highly nonlinear, coupled, and unstable machines. They have fast response and controlling them is very complicated and need high degree of precision. In this paper, a detailed nonlinear model is derived. The derived nonlinear model is linearized around a nominal point in the hovering state and a linear classical controller is designed. Then, an optimization algorithm is applied where the linear controller's parameters are adjusted offline so that the Integral Time-multiplied Square Error (ITSE), the error between the output response of the nonlinear system and the reference signal, is minimal. Both the linear and the optimized controllers are augmented with the nonlinear model and the simulation results are compared.