{"title":"基于神经网络的无人机能效优化控制算法","authors":"A. Korneyev, M. Gorobetz","doi":"10.1109/RTUCON51174.2020.9316556","DOIUrl":null,"url":null,"abstract":"One of the important problems in the field of unmanned autonomous vehicles (UAV) is energy efficiency. By the results of this research authors contribute to development of energy efficient control system of the UAV. Energy consumption of the UAV is optimized by implementation of neural network based algorithm used to control electric drive. Additional UAV optimization controller is proposed for energy efficient flight control. Neural network based structure extends the adaptive search algorithm allowing significantly reduce time to find out the value of optimal control signals and maximize energy efficiency of the UAV.","PeriodicalId":332414,"journal":{"name":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Neural Network Based UAV Optimal Control Algorithm for Energy Efficiency Maximization\",\"authors\":\"A. Korneyev, M. Gorobetz\",\"doi\":\"10.1109/RTUCON51174.2020.9316556\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the important problems in the field of unmanned autonomous vehicles (UAV) is energy efficiency. By the results of this research authors contribute to development of energy efficient control system of the UAV. Energy consumption of the UAV is optimized by implementation of neural network based algorithm used to control electric drive. Additional UAV optimization controller is proposed for energy efficient flight control. Neural network based structure extends the adaptive search algorithm allowing significantly reduce time to find out the value of optimal control signals and maximize energy efficiency of the UAV.\",\"PeriodicalId\":332414,\"journal\":{\"name\":\"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RTUCON51174.2020.9316556\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTUCON51174.2020.9316556","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neural Network Based UAV Optimal Control Algorithm for Energy Efficiency Maximization
One of the important problems in the field of unmanned autonomous vehicles (UAV) is energy efficiency. By the results of this research authors contribute to development of energy efficient control system of the UAV. Energy consumption of the UAV is optimized by implementation of neural network based algorithm used to control electric drive. Additional UAV optimization controller is proposed for energy efficient flight control. Neural network based structure extends the adaptive search algorithm allowing significantly reduce time to find out the value of optimal control signals and maximize energy efficiency of the UAV.