Stability and Performance Analysis of Six-Rotor Unmanned Aerial Vehicles in Wind Disturbance

2018 ◽  
Vol 13 (3) ◽  
Author(s):  
Xianying Li ◽  
Biao Zhao ◽  
Yu Yao ◽  
Hongtao Wu ◽  
Yunping Liu
Keyword(s):  
Performance Analysis ◽  
Simulation Model ◽  
Unmanned Aerial Vehicles ◽  
Lyapunov Exponents ◽  
Wind Disturbance ◽  
Flight Experiment ◽  
Aerial Vehicles ◽  
Simulation Results ◽  
And Performance ◽  
The Stability

The effect of wind disturbances on the stability of six-rotor unmanned aerial vehicles (UAVs) was investigated, exploring the various disturbances in different directions. The simulation model-based Euler–Poincare equation was established to investigate the spectra of Lyapunov exponents. Next, the value of the Lyapunov exponents was used to evaluate the stability of the systems. The results obtained show that the various speeds of rotors are optimized to keep up the stability after disturbances. In addition, the flight experiment with the hitting gust has been carried out to verify the validity and accuracy of the simulation results.

Stability and performance analysis of unmanned aerial vehicles: Quadrotor against Hexrotor

2015 ◽  
Vol 9 (8) ◽  
pp. 1190-1196 ◽  
Author(s):  
Jonay Toledo ◽  
Daniel Perea ◽  
Leopoldo Acosta ◽  
Nestor Morales
Keyword(s):  
Performance Analysis ◽  
Unmanned Aerial Vehicles ◽  
Aerial Vehicles ◽  
And Performance

scholarly journals Deep Learning Based BackCom Multiple Beamforming for 6G UAV IoT Networks

2020 ◽  
Author(s):  
Fei Qi ◽  
Wenjing Li ◽  
Peng Yu ◽  
Lei Feng ◽  
Fanqin Zhou
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Unmanned Aerial Vehicles ◽  
Communication Technologies ◽  
Obvious Advantage ◽  
Iot Applications ◽  
Reflective Surface ◽  
Aerial Vehicles ◽  
Simulation Results ◽  
And Performance

Abstract Combining unmanned aerial vehicles (UAVs) with 6G, Internet of Things (IoT) and other emerging communication technologies could better satisfy various IoT applications and create more innovative services. This paper develops a novel hierarchical 6G IoT network with UAVs in the sky and intelligent reflective surface (IRS) equipped. The system employs backscattering communication (BackCom) to transmit data in a free-ride manner. Through beamforming, IRS enhances the energy of the reflectable signal, thereby improving the distance and performance of the BackCom. Simulation results reveal that our approach makes a significant improvement to the performance of the whole system, and takes obvious advantage over traditional solutions.

scholarly journals Deep learning-based BackCom multiple beamforming for 6G UAV IoT networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Fei Qi ◽  
Wenjing Li ◽  
Peng Yu ◽  
Lei Feng ◽  
Fanqin Zhou
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Unmanned Aerial Vehicles ◽  
Communication Technologies ◽  
Obvious Advantage ◽  
Iot Applications ◽  
Reflective Surface ◽  
Aerial Vehicles ◽  
Simulation Results ◽  
And Performance

AbstractCombining unmanned aerial vehicles (UAVs) with 6G, Internet of Things (IoT) and other emerging communication technologies could better satisfy various IoT applications and create more innovative services. This paper develops a novel hierarchical 6G IoT network with UAVs in the sky and intelligent reflective surface (IRS) equipped. The system employs backscattering communication (BackCom) to transmit data in a free-ride manner. Through beamforming, IRS enhances the energy of the reflectable signal, thereby improving the distance and performance of the BackCom. Simulation results reveal that our approach makes a significant improvement to the performance of the whole system and takes obvious advantage over traditional solutions.

scholarly journals Deep Learning Based BackCom Multiple Beamforming for 6G UAV IoT Networks

2021 ◽  
Author(s):  
Fei Qi ◽  
Wenjing Li ◽  
Peng Yu ◽  
Lei Feng ◽  
Fanqin Zhou
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Unmanned Aerial Vehicles ◽  
Communication Technologies ◽  
Obvious Advantage ◽  
Iot Applications ◽  
Reflective Surface ◽  
Aerial Vehicles ◽  
Simulation Results ◽  
And Performance

Abstract Combining unmanned aerial vehicles (UAVs) with 6G, Internet of Things (IoT) and other emerging communication technologies could better satisfy various IoT applications and create more innovative services. This paper develops a novel hierarchical 6G IoT network with UAVs in the sky and intelligent reflective surface (IRS) equipped. The system employs backscattering communication (BackCom) to transmit data in a free-ride manner. Through beamforming, IRS enhances the energy of the reflectable signal, thereby improving the distance and performance of the BackCom. Simulation results reveal that our approach makes a significant improvement to the performance of the whole system, and takes obvious advantage over traditional solutions.

Intelligent cooperative collision avoidance via fuzzy potential fields

Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
Daegyun Choi ◽  
Anirudh Chhabra ◽  
Donghoon Kim
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Fuzzy Inference ◽  
Potential Fields ◽  
Rule Base ◽  
Local Minima ◽  
Inference System ◽  
Aerial Vehicles ◽  
Different Shapes ◽  
Simulation Results

Summary This paper proposes an intelligent cooperative collision avoidance approach combining the enhanced potential field (EPF) with a fuzzy inference system (FIS) to resolve local minima and goal non-reachable with obstacles nearby issues and provide a near-optimal collision-free trajectory. A genetic algorithm is utilized to optimize parameters of membership function and rule base of the FISs. This work uses a single scenario containing all issues and interactions among unmanned aerial vehicles (UAVs) for training. For validating the performance, two scenarios containing obstacles with different shapes and several UAVs in small airspace are considered. Multiple simulation results show that the proposed approach outperforms the conventional EPF approach statistically.

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