{"title":"基于智能控制器的非线性直升机模型轴向控制","authors":"A. Chaudhary","doi":"10.1109/ICONAT57137.2023.10080707","DOIUrl":null,"url":null,"abstract":"Adaptive neuro-fuzzy inference system (ANFIS) based intelligent control is employed on a helicopter system in this paper. This helps to control the alterations of the pitch axis and yaw axis of helicopter, with the reference trajectory. Two different ANFIS logic modules are developed, one is to help adjust the angle variations in pitch axis and other is to help adjusting the yaw axis angle variations of a two degree of freedom (2 DOF) Quanser Helicopter system, so that the altitude and angular speed are controlled altogether. The whole execution framework utilizes standard configurations of MATLAB platform and simulation toolboxes. The results obtained in the process are then compared with the traditional LQR Controller and Fuzzy Controller on simulation platform.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Axis Control of a Nonlinear Helicopter Model Using Intelligent Controller\",\"authors\":\"A. Chaudhary\",\"doi\":\"10.1109/ICONAT57137.2023.10080707\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Adaptive neuro-fuzzy inference system (ANFIS) based intelligent control is employed on a helicopter system in this paper. This helps to control the alterations of the pitch axis and yaw axis of helicopter, with the reference trajectory. Two different ANFIS logic modules are developed, one is to help adjust the angle variations in pitch axis and other is to help adjusting the yaw axis angle variations of a two degree of freedom (2 DOF) Quanser Helicopter system, so that the altitude and angular speed are controlled altogether. The whole execution framework utilizes standard configurations of MATLAB platform and simulation toolboxes. The results obtained in the process are then compared with the traditional LQR Controller and Fuzzy Controller on simulation platform.\",\"PeriodicalId\":250587,\"journal\":{\"name\":\"2023 International Conference for Advancement in Technology (ICONAT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference for Advancement in Technology (ICONAT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICONAT57137.2023.10080707\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference for Advancement in Technology (ICONAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONAT57137.2023.10080707","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Axis Control of a Nonlinear Helicopter Model Using Intelligent Controller
Adaptive neuro-fuzzy inference system (ANFIS) based intelligent control is employed on a helicopter system in this paper. This helps to control the alterations of the pitch axis and yaw axis of helicopter, with the reference trajectory. Two different ANFIS logic modules are developed, one is to help adjust the angle variations in pitch axis and other is to help adjusting the yaw axis angle variations of a two degree of freedom (2 DOF) Quanser Helicopter system, so that the altitude and angular speed are controlled altogether. The whole execution framework utilizes standard configurations of MATLAB platform and simulation toolboxes. The results obtained in the process are then compared with the traditional LQR Controller and Fuzzy Controller on simulation platform.