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Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I

Research Article

Decentralized Control Method for UAV Arriving Simultaneously Based on Large Data Analysis

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  • @INPROCEEDINGS{10.1007/978-3-030-67871-5_18,
        author={Jian-jun Zhu and Jun Zhang},
        title={Decentralized Control Method for UAV Arriving Simultaneously Based on Large Data Analysis},
        proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I},
        proceedings_a={ADHIP},
        year={2021},
        month={2},
        keywords={Large data analysis UAV Decentralized control},
        doi={10.1007/978-3-030-67871-5_18}
    }
    
  • Jian-jun Zhu
    Jun Zhang
    Year: 2021
    Decentralized Control Method for UAV Arriving Simultaneously Based on Large Data Analysis
    ADHIP
    Springer
    DOI: 10.1007/978-3-030-67871-5_18
Jian-jun Zhu1, Jun Zhang1,*
  • 1: College of Electrical Engineering, Zhengzhou University of Science and Technology
*Contact email: zhaoxia1812@163.com

Abstract

Due to the limitation of the control method during the conventional simultaneous arrival control drone, a certain deviation is caused. In order to solve such problems, a research on the decentralized control method of simultaneous arrival drone based on big data analysis is proposed. Fusion of decentralized information is achieved through information filtering. Based on this, decentralized coordination of formations is controlled. The optimal path and convergence speed are calculated by calculation. Decentralized control methods are implemented through communication delay constraints. The proposed method is used for simulation experiments and it is found that the method can effectively reduce the error, which fully proves the feasibility of the control method.

Keywords
Large data analysis UAV Decentralized control
Published
2021-02-03
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-67871-5_18
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