کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7116566 | 1461184 | 2017 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Outdoor flocking of quadcopter drones with decentralized model predictive control
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موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
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چکیده انگلیسی
In this paper, we present a multi-drone system featured with a decentralized model predictive control (DMPC) flocking algorithm. The drones gather localized information from neighbors and update their velocities using the DMPC flocking algorithm. In the multi-drone system, data packages are transmitted through XBee® wireless modules in broadcast mode, yielding such an anonymous and decentralized system where all the calculations and controls are completed on an onboard minicomputer of each drone. Each drone is a double-layered agent system with the coordination layer running multi-drone flocking algorithms and the flight control layer navigating the drone, and the final formation of the flock relies on both the communication range and the desired inter-drone distance. We give both numerical simulations and field tests with a flock of five drones, showing that the DMPC flocking algorithm performs well on the presented multi-drone system in both the convergence rate and the ability of tracking a desired path.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISA Transactions - Volume 71, Part 1, November 2017, Pages 84-92
Journal: ISA Transactions - Volume 71, Part 1, November 2017, Pages 84-92
نویسندگان
Quan Yuan, Jingyuan Zhan, Xiang Li,