{"title":"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","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":"{\"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}","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}
Self balancing robot using complementary filter: Implementation and analysis of complementary filter on SBR
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.