Luoyu Zhang, Zhiwei Wen, Xinsong Zhang, Yunxiang Guo, Cheng Lu
{"title":"基于神经扰动观测器的陀螺神经滑模控制","authors":"Luoyu Zhang, Zhiwei Wen, Xinsong Zhang, Yunxiang Guo, Cheng Lu","doi":"10.1109/RCAE56054.2022.9996049","DOIUrl":null,"url":null,"abstract":"In this paper, a neural network sliding mode control based on neural network disturbance observer is proposed for the control of MEMS gyroscopes under external disturbances. In the design process, two sets of RBF neural networks are incorporated in the sliding mode controller design as well as the disturbance design separately to release the dependence of each module on gyroscope system parameters. Meanwhile, the integration of the neural disturbance observer can help to alleviate chattering phenomenon in conventional sliding mode control forces. Simulation studies are implemented to verify the effectiveness of the proposed control scheme.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"491 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Neural Sliding Mode Control using Neural Disturbance Observer for Gyroscopes\",\"authors\":\"Luoyu Zhang, Zhiwei Wen, Xinsong Zhang, Yunxiang Guo, Cheng Lu\",\"doi\":\"10.1109/RCAE56054.2022.9996049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a neural network sliding mode control based on neural network disturbance observer is proposed for the control of MEMS gyroscopes under external disturbances. In the design process, two sets of RBF neural networks are incorporated in the sliding mode controller design as well as the disturbance design separately to release the dependence of each module on gyroscope system parameters. Meanwhile, the integration of the neural disturbance observer can help to alleviate chattering phenomenon in conventional sliding mode control forces. Simulation studies are implemented to verify the effectiveness of the proposed control scheme.\",\"PeriodicalId\":165439,\"journal\":{\"name\":\"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)\",\"volume\":\"491 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RCAE56054.2022.9996049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RCAE56054.2022.9996049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neural Sliding Mode Control using Neural Disturbance Observer for Gyroscopes
In this paper, a neural network sliding mode control based on neural network disturbance observer is proposed for the control of MEMS gyroscopes under external disturbances. In the design process, two sets of RBF neural networks are incorporated in the sliding mode controller design as well as the disturbance design separately to release the dependence of each module on gyroscope system parameters. Meanwhile, the integration of the neural disturbance observer can help to alleviate chattering phenomenon in conventional sliding mode control forces. Simulation studies are implemented to verify the effectiveness of the proposed control scheme.