{"title":"基于RBF神经网络的水下机器人自适应滑模控制系统设计","authors":"Wei Chen, S. Hu, Qingyu Wei","doi":"10.1109/CCDC52312.2021.9602771","DOIUrl":null,"url":null,"abstract":"The dynamic positioning control of ROV near the water surface under wave disturbance is still a challenging problem. The principle of sliding mode control and the method of approximating unknown function by RBF neural network are studied. The adaptive sliding mode controller of RBF neural network is designed. The stability and convergence of the proposed algorithm are deduced and verified, and compared with the simulation results of traditional adaptive sliding mode control methods. The simulation results show that the ROV's trajectory tracking effect is good in the wave disturbance environment. The experimental results prove the effectiveness of the method and achieved satisfactory performance.","PeriodicalId":143976,"journal":{"name":"2021 33rd Chinese Control and Decision Conference (CCDC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design of ROV Adaptive Sliding Mode Control System for Underwater Vehicle Based on RBF Neural Network\",\"authors\":\"Wei Chen, S. Hu, Qingyu Wei\",\"doi\":\"10.1109/CCDC52312.2021.9602771\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The dynamic positioning control of ROV near the water surface under wave disturbance is still a challenging problem. The principle of sliding mode control and the method of approximating unknown function by RBF neural network are studied. The adaptive sliding mode controller of RBF neural network is designed. The stability and convergence of the proposed algorithm are deduced and verified, and compared with the simulation results of traditional adaptive sliding mode control methods. The simulation results show that the ROV's trajectory tracking effect is good in the wave disturbance environment. The experimental results prove the effectiveness of the method and achieved satisfactory performance.\",\"PeriodicalId\":143976,\"journal\":{\"name\":\"2021 33rd Chinese Control and Decision Conference (CCDC)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 33rd Chinese Control and Decision Conference (CCDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCDC52312.2021.9602771\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 33rd Chinese Control and Decision Conference (CCDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCDC52312.2021.9602771","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of ROV Adaptive Sliding Mode Control System for Underwater Vehicle Based on RBF Neural Network
The dynamic positioning control of ROV near the water surface under wave disturbance is still a challenging problem. The principle of sliding mode control and the method of approximating unknown function by RBF neural network are studied. The adaptive sliding mode controller of RBF neural network is designed. The stability and convergence of the proposed algorithm are deduced and verified, and compared with the simulation results of traditional adaptive sliding mode control methods. The simulation results show that the ROV's trajectory tracking effect is good in the wave disturbance environment. The experimental results prove the effectiveness of the method and achieved satisfactory performance.