{"title":"Modeling and controller design for helicopter dynamics","authors":"Abdur Rasheed","doi":"10.1109/ICOSST.2017.8278997","DOIUrl":null,"url":null,"abstract":"This work addresses comprehensive modeling of a helicopter coupled dynamics and longitudinal and lateral models for hovering dynamics. Non-linear models obtained using Newtonian mechanics are linearized using small perturbation theory and converted to state space models. These models are implemented in Matlab/Simulink and simulation results are obtained. The different types of control techniques implemented for these models include Linear Quadratic Regulator (LQR), Linear Quadratic Gaussian (LQG) control and Linear Matrix Inequalities (LMIs). These control strategies significantly improve performance of these models.","PeriodicalId":414131,"journal":{"name":"2017 International Conference on Open Source Systems & Technologies (ICOSST)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Open Source Systems & Technologies (ICOSST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSST.2017.8278997","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This work addresses comprehensive modeling of a helicopter coupled dynamics and longitudinal and lateral models for hovering dynamics. Non-linear models obtained using Newtonian mechanics are linearized using small perturbation theory and converted to state space models. These models are implemented in Matlab/Simulink and simulation results are obtained. The different types of control techniques implemented for these models include Linear Quadratic Regulator (LQR), Linear Quadratic Gaussian (LQG) control and Linear Matrix Inequalities (LMIs). These control strategies significantly improve performance of these models.