{"title":"两轮自平衡机器人控制策略研究","authors":"Y. Gong, Xiao Wu, Huijiao Ma","doi":"10.1109/CSMA.2015.63","DOIUrl":null,"url":null,"abstract":"The structure of two-wheeled self-balancing robot is equivalent to the combination of the linear inverted pendulum and wheeled mobile robot. But compared to the linear inverted pendulum, two-wheeled self-balancing robot can move freely and turn flexibly. So the system is more complex and difficult to control. As the two-wheeled self-balancing robot is a high order and multi variable system, PID controller based on output feedback can't have a satisfactory control effect. The LQR control strategy is implemented, and the weight matrix Q and R of the LQR controller are optimized by using multi-population genetic ideas. Taking two wheeled self balancing robot as the test platform, the two control modes of LQR and PID are used to carry out experiments and analysis. In the simulation experiments of balance control, position control and speed control, the LQR controller has a better performance in the system's robustness and fast response.","PeriodicalId":205396,"journal":{"name":"2015 International Conference on Computer Science and Mechanical Automation (CSMA)","volume":"4 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Research on Control Strategy of Two-Wheeled Self-Balancing Robot\",\"authors\":\"Y. Gong, Xiao Wu, Huijiao Ma\",\"doi\":\"10.1109/CSMA.2015.63\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The structure of two-wheeled self-balancing robot is equivalent to the combination of the linear inverted pendulum and wheeled mobile robot. But compared to the linear inverted pendulum, two-wheeled self-balancing robot can move freely and turn flexibly. So the system is more complex and difficult to control. As the two-wheeled self-balancing robot is a high order and multi variable system, PID controller based on output feedback can't have a satisfactory control effect. The LQR control strategy is implemented, and the weight matrix Q and R of the LQR controller are optimized by using multi-population genetic ideas. Taking two wheeled self balancing robot as the test platform, the two control modes of LQR and PID are used to carry out experiments and analysis. In the simulation experiments of balance control, position control and speed control, the LQR controller has a better performance in the system's robustness and fast response.\",\"PeriodicalId\":205396,\"journal\":{\"name\":\"2015 International Conference on Computer Science and Mechanical Automation (CSMA)\",\"volume\":\"4 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Computer Science and Mechanical Automation (CSMA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSMA.2015.63\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Computer Science and Mechanical Automation (CSMA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSMA.2015.63","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Control Strategy of Two-Wheeled Self-Balancing Robot
The structure of two-wheeled self-balancing robot is equivalent to the combination of the linear inverted pendulum and wheeled mobile robot. But compared to the linear inverted pendulum, two-wheeled self-balancing robot can move freely and turn flexibly. So the system is more complex and difficult to control. As the two-wheeled self-balancing robot is a high order and multi variable system, PID controller based on output feedback can't have a satisfactory control effect. The LQR control strategy is implemented, and the weight matrix Q and R of the LQR controller are optimized by using multi-population genetic ideas. Taking two wheeled self balancing robot as the test platform, the two control modes of LQR and PID are used to carry out experiments and analysis. In the simulation experiments of balance control, position control and speed control, the LQR controller has a better performance in the system's robustness and fast response.