Position & Attitude Control of an Aerial Robot (Quadrotor) With Intelligent PID and State feedback LQR Controller: A Comparative Approach

M. Shehzad, A. Bilal, Hasnain Ahmad
{"title":"Position & Attitude Control of an Aerial Robot (Quadrotor) With Intelligent PID and State feedback LQR Controller: A Comparative Approach","authors":"M. Shehzad, A. Bilal, Hasnain Ahmad","doi":"10.1109/IBCAST.2019.8667170","DOIUrl":null,"url":null,"abstract":"The Quadcopter Helicopters due to their unmatchable stability in Unmanned Aerial vehicle (UAV) class have gained control engineering community attraction during the last decade. It is an under actuated system with four inputs and six output states. Quadrotors are famous in route control and they can also be used as a testbed for testing, authentication and validation of control engineering laws in simulation and in a real-time environment. Testing, Authentication and Validation of a novel and proposed control algorithm is a pre requisite in Simulation on a plant with use of mathematical engineering tool i.e. LabVIEW or MATLAB. The Model of a plant can be chosen with reference to the proposed algorithm, so it can be linear or nonlinear. This proposed research work is a contribution in field of Intelligent flight controller Implementation and their comparison on Unmanned Aerial Vehicles (UAVs) family. This research work presents the implementation of Intelligent flight PID, LQR and State feedback controllers on nonlinear model of X3D Quadrotor. The implemented controllers have been tested, authenticated, validated and also compared in simulation using NI LabVIEW. The Control algorithms are implemented in a closed loop background to control the position & attitude of trajectory following Quadrotor Helicopter. To make the PID, LQR and state feedback control more challengeable, the model uncertainty and sensor noise has also been added to the plant. Although all the implemented controllers gives satisfactory feedback in stabilizing the quadrotor, but the comparison shows that the LQR controller because of its best performance, effectiveness and robustness in the plant, seems to be the best comparative implemented controller among them.","PeriodicalId":335329,"journal":{"name":"2019 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IBCAST.2019.8667170","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

The Quadcopter Helicopters due to their unmatchable stability in Unmanned Aerial vehicle (UAV) class have gained control engineering community attraction during the last decade. It is an under actuated system with four inputs and six output states. Quadrotors are famous in route control and they can also be used as a testbed for testing, authentication and validation of control engineering laws in simulation and in a real-time environment. Testing, Authentication and Validation of a novel and proposed control algorithm is a pre requisite in Simulation on a plant with use of mathematical engineering tool i.e. LabVIEW or MATLAB. The Model of a plant can be chosen with reference to the proposed algorithm, so it can be linear or nonlinear. This proposed research work is a contribution in field of Intelligent flight controller Implementation and their comparison on Unmanned Aerial Vehicles (UAVs) family. This research work presents the implementation of Intelligent flight PID, LQR and State feedback controllers on nonlinear model of X3D Quadrotor. The implemented controllers have been tested, authenticated, validated and also compared in simulation using NI LabVIEW. The Control algorithms are implemented in a closed loop background to control the position & attitude of trajectory following Quadrotor Helicopter. To make the PID, LQR and state feedback control more challengeable, the model uncertainty and sensor noise has also been added to the plant. Although all the implemented controllers gives satisfactory feedback in stabilizing the quadrotor, but the comparison shows that the LQR controller because of its best performance, effectiveness and robustness in the plant, seems to be the best comparative implemented controller among them.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于智能PID和状态反馈LQR控制器的四旋翼航空机器人位置姿态控制比较研究
四旋翼直升机由于其在无人驾驶飞行器(UAV)类中无可比拟的稳定性,在过去十年中获得了控制工程界的关注。它是一个欠驱动系统,具有四个输入和六个输出状态。四旋翼飞行器在航路控制方面非常有名,它们也可以作为一个试验台,在仿真和实时环境中对控制工程规律进行测试、验证和验证。使用数学工程工具(如LabVIEW或MATLAB)对工厂进行仿真时,对新提出的控制算法进行测试、认证和验证是先决条件。可以根据所提出的算法选择对象的模型,因此模型可以是线性的,也可以是非线性的。本文的研究工作对智能飞行控制器的实现及其在无人机系列上的比较研究有一定的贡献。本文研究了在X3D四旋翼非线性模型上实现智能飞行PID、LQR和状态反馈控制器。采用NI LabVIEW对所实现的控制器进行了测试、验证和验证,并进行了仿真比较。控制算法是在闭环背景下实现的,用于控制四旋翼直升机跟踪轨迹的位置和姿态。为了使PID、LQR和状态反馈控制更具挑战性,模型不确定性和传感器噪声也被加入到对象中。虽然所有实现的控制器在稳定四旋翼飞行器方面都给出了满意的反馈,但比较表明,LQR控制器由于其在对象内的最佳性能、有效性和鲁棒性,似乎是其中最好的比较实现控制器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Comparative Survey of Techniques and Technologies Used in Transmit Path of Transmit Receive Module of AESA Radar Testing-based Model Learning Approach for Legacy Components Pic Microcontroller Based Power Factor Correction for both Leading and Lagging Loads using Compensation Method Speed Tracking of Spark Ignition Engines using Higher Order Sliding Mode Control Survey of Authentication Schemes for Health Monitoring: A Subset of Cyber Physical System
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1