Yuxin Hu, Changlin Liu, Ping Wang, Mengping Zhang, Han Mu, Quan Yuan
{"title":"基于参数优化自抗扰控制器的多无人机编队控制","authors":"Yuxin Hu, Changlin Liu, Ping Wang, Mengping Zhang, Han Mu, Quan Yuan","doi":"10.1109/ccis57298.2022.10016414","DOIUrl":null,"url":null,"abstract":"This paper considers the problem of multiple unmanned aerial vehicles (UAVs) formation in a wind disturbance environment. An anti-disturbance formation control method is proposed to prevent environmental disturbance while ensuring the formation. By introducing the active disturbance rejection control (ADRC) of each UAV in the consensus-based algorithm structure, the stability of the formation system can be significantly improved. Moreover, particle swarm optimization (PSO) is used to optimize the connection weight between ADRC and consensus control, to ensure that the advantages of the two control theories are better combined, so that the controlled system has stronger robustness and better dynamic quality. Finally, a simulation example is provided to verify the effectiveness of the control method.","PeriodicalId":374660,"journal":{"name":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Multi-UAV Formation Control Based on Parameter Optimization ADRC\",\"authors\":\"Yuxin Hu, Changlin Liu, Ping Wang, Mengping Zhang, Han Mu, Quan Yuan\",\"doi\":\"10.1109/ccis57298.2022.10016414\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper considers the problem of multiple unmanned aerial vehicles (UAVs) formation in a wind disturbance environment. An anti-disturbance formation control method is proposed to prevent environmental disturbance while ensuring the formation. By introducing the active disturbance rejection control (ADRC) of each UAV in the consensus-based algorithm structure, the stability of the formation system can be significantly improved. Moreover, particle swarm optimization (PSO) is used to optimize the connection weight between ADRC and consensus control, to ensure that the advantages of the two control theories are better combined, so that the controlled system has stronger robustness and better dynamic quality. Finally, a simulation example is provided to verify the effectiveness of the control method.\",\"PeriodicalId\":374660,\"journal\":{\"name\":\"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ccis57298.2022.10016414\",\"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 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ccis57298.2022.10016414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-UAV Formation Control Based on Parameter Optimization ADRC
This paper considers the problem of multiple unmanned aerial vehicles (UAVs) formation in a wind disturbance environment. An anti-disturbance formation control method is proposed to prevent environmental disturbance while ensuring the formation. By introducing the active disturbance rejection control (ADRC) of each UAV in the consensus-based algorithm structure, the stability of the formation system can be significantly improved. Moreover, particle swarm optimization (PSO) is used to optimize the connection weight between ADRC and consensus control, to ensure that the advantages of the two control theories are better combined, so that the controlled system has stronger robustness and better dynamic quality. Finally, a simulation example is provided to verify the effectiveness of the control method.