Self balancing robot using complementary filter: Implementation and analysis of complementary filter on SBR

Kartik Madhira, A. Gandhi, Aneesha Gujral
{"title":"Self balancing robot using complementary filter: Implementation and analysis of complementary filter on SBR","authors":"Kartik Madhira, A. Gandhi, Aneesha Gujral","doi":"10.1109/ICEEOT.2016.7755240","DOIUrl":null,"url":null,"abstract":"The Self balancing robot is based on the inverted pendulum concept, wherein an inverted pendulum is positioned on a cart and the cart is allowed to move on the horizontal axis so as to keep the pendulum in the upright position. This is a classic case of an unstable system. The angle measurement with the help of a fusion of gyroscope and accelerometer requires filtering mechanism as both provide erroneous angle results. Kalman filter is one such filter, but the design and implementation of such a filter is lengthy, tiresome and difficult to implement on smaller 8-bit micro controllers. Thus, this paper intends to design and implement a Self balancing robot with the help of a complementary filter and its analysis using different filter coefficients using PID algorithm as the control strategy. The robot is powered with a lithium-polymer battery to drive the motors.","PeriodicalId":383674,"journal":{"name":"2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEOT.2016.7755240","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

The Self balancing robot is based on the inverted pendulum concept, wherein an inverted pendulum is positioned on a cart and the cart is allowed to move on the horizontal axis so as to keep the pendulum in the upright position. This is a classic case of an unstable system. The angle measurement with the help of a fusion of gyroscope and accelerometer requires filtering mechanism as both provide erroneous angle results. Kalman filter is one such filter, but the design and implementation of such a filter is lengthy, tiresome and difficult to implement on smaller 8-bit micro controllers. Thus, this paper intends to design and implement a Self balancing robot with the help of a complementary filter and its analysis using different filter coefficients using PID algorithm as the control strategy. The robot is powered with a lithium-polymer battery to drive the motors.
基于互补滤波器的自平衡机器人:互补滤波器在SBR上的实现与分析
自平衡机器人基于倒立摆的概念,将倒立摆放置在小车上,小车沿水平轴移动,使倒立摆保持直立位置。这是一个不稳定系统的典型例子。在陀螺仪和加速度计融合的角度测量中,由于两者都会产生误差,因此需要滤波机制。卡尔曼滤波器就是这样一种滤波器,但是这种滤波器的设计和实现是冗长的,令人厌烦的,并且难以在较小的8位微控制器上实现。因此,本文拟采用PID算法作为控制策略,利用互补滤波器及其不同滤波系数的分析,设计并实现一种自平衡机器人。该机器人由一块锂聚合物电池驱动马达。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信