Spherical calibration and quality control of ground and UAV vector magnetometer data

2021 ◽  
Vol 40 (5) ◽  
pp. 382a1-382a6
Author(s):  
Ed Cunion
Keyword(s):  
Urban System ◽  
Rural And Urban ◽  
Ground Survey ◽  
Scalar Magnetometer ◽  
Vector Magnetometer ◽  
Magnetometer Data ◽  
Aerial Vehicle ◽  
Survey Results ◽  
And Control ◽  
Airborne Magnetic

Ground traverse and unmanned aerial vehicle (UAV) airborne magnetic mapping results covering an urban landfill are compared for a picoTesla-resolution fluxgate vector magnetometer (FVM). Rural and urban system noise tests are undertaken first to develop FVM quality assessment and control methods that are then used for processing the landfill survey data. The FVM ground and UAV survey results are subsequently compared with a femtoTesla-resolution alkali-vapor scalar magnetometer ground survey that provides a scalar total magnetic intensity image reference standard.

Applying coherent design to uninhabited aerial vehicle operations and control stations

2007 ◽  
Author(s):  
Luis N. Gonzalez Castro ◽  
Amy R. Pritchett ◽  
Daniel P. J. Bruneau ◽  
Eric N. Johnson
Keyword(s):  
Aerial Vehicle ◽  
And Control

Modeling and control of a quadrotor tail-sitter unmanned aerial vehicles

2021 ◽  
pp. 095965182110504
Author(s):  
Hongbo Xin ◽  
Yujie Wang ◽  
Xianzhong Gao ◽  
Qingyang Chen ◽  
Bingjie Zhu ◽  
...  
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Euler Angle ◽  
Level Flight ◽  
Aerial Vehicles ◽  
Flight Mode ◽  
Aerial Vehicle ◽  
Hover Flight ◽  
And Control

The tail-sitter unmanned aerial vehicles have the advantages of multi-rotors and fixed-wing aircrafts, such as vertical takeoff and landing, long endurance and high-speed cruise. These make the tail-sitter unmanned aerial vehicle capable for special tasks in complex environments. In this article, we present the modeling and the control system design for a quadrotor tail-sitter unmanned aerial vehicle whose main structure consists of a traditional quadrotor with four wings fixed on the four rotor arms. The key point of the control system is the transition process between hover flight mode and level flight mode. However, the normal Euler angle representation cannot tackle both of the hover and level flight modes because of the singularity when pitch angle tends to [Formula: see text]. The dual-Euler method using two Euler-angle representations in two body-fixed coordinate frames is presented to couple with this problem, which gives continuous attitude representation throughout the whole flight envelope. The control system is divided into hover and level controllers to adapt to the two different flight modes. The nonlinear dynamic inverse method is employed to realize fuselage rotation and attitude stabilization. In guidance control, the vector field method is used in level flight guidance logic, and the quadrotor guidance method is used in hover flight mode. The framework of the whole system is established by MATLAB and Simulink, and the effectiveness of the guidance and control algorithms are verified by simulation. Finally, the flight test of the prototype shows the feasibility of the whole system.

scholarly journals Dynamic Stability and Control of a Manipulating Unmanned Aerial Vehicle

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Yunping Liu ◽  
Xijie Huang ◽  
Yonghong Zhang ◽  
Yukang Zhou
Keyword(s):  
Stability Analysis ◽  
Lyapunov Exponent ◽  
Dynamic Stability ◽  
Unmanned Aerial Vehicle ◽  
Impedance Control ◽  
System Stability ◽  
Constructive Method ◽  
Aerial Vehicle ◽  
And Control ◽  
The Impact

This paper focuses on the dynamic stability analysis of a manipulator mounted on a quadrotor unmanned aerial vehicle, namely, a manipulating unmanned aerial vehicle (MUAV). Manipulator movements and environments interaction will extremely affect the dynamic stability of the MUAV system. So the dynamic stability analysis of the MUAV system is of paramount importance for safety and satisfactory performance. However, the applications of Lyapunov’s stability theory to the MUAV system have been extremely limited, due to the lack of a constructive method available for deriving a Lyapunov function. Thus, Lyapunov exponent method and impedance control are introduced, and the Lyapunov exponent method can establish the quantitative relationships between the manipulator movements and the dynamics stability, while impedance control can reduce the impact of environmental interaction on system stability. Numerical simulation results have demonstrated the effectiveness of the proposed method.

Development of Autonomous Quad-Tilt-Wing (QTW) Unmanned Aerial Vehicle: Design, Modeling, and Control

2010 ◽  
pp. 77-93 ◽  
Author(s):  
Kenzo Nonami ◽  
Farid Kendoul ◽  
Satoshi Suzuki ◽  
Wei Wang ◽  
Daisuke Nakazawa
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Vehicle Design ◽  
Modeling And Control ◽  
Aerial Vehicle ◽  
And Control

Dynamic Modeling and Control Techniques for a Quadrotor

2019 ◽  
pp. 20-66
Author(s):  
Heba Elkholy ◽  
Maki K. Habib
Keyword(s):  
Pid Controller ◽  
Degrees Of Freedom ◽  
Sliding Mode ◽  
Dynamic Performance ◽  
Simulation Environment ◽  
Modeling And Control ◽  
Controller Gain ◽  
Aerial Vehicle ◽  
And Control ◽  
The Mathematical Model

This chapter presents the detailed dynamic model of a Vertical Take-Off and Landing (VTOL) type Unmanned Aerial Vehicle (UAV) known as the quadrotor. The mathematical model is derived based on Newton Euler formalism. This is followed by the development of a simulation environment on which the developed model is verified. Four control algorithms are developed to control the quadrotor's degrees of freedom: a linear PID controller, Gain Scheduling-based PID controller, nonlinear Sliding Mode, and Backstepping controllers. The performances of these controllers are compared through the developed simulation environment in terms of their dynamic performance, stability, and the effect of possible disturbances.

Modeling and control of a quadrotor unmanned aerial vehicle using type-2 fuzzy systems

2021 ◽  
pp. 25-46
Author(s):  
Ayad Al-Mahturi ◽  
Fendy Santoso ◽  
Matthew A. Garratt ◽  
Sreenatha G. Anavatti
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Fuzzy Systems ◽  
Modeling And Control ◽  
Aerial Vehicle ◽  
And Control

Survey on Aerial Manipulator: System, Modeling, and Control

Robotica ◽  
2019 ◽  
Vol 38 (7) ◽  
pp. 1288-1317 ◽  
Author(s):  
Xiangdong Meng ◽  
Yuqing He ◽  
Jianda Han
Keyword(s):  
System Modeling ◽  
Future Research ◽  
Typical Application ◽  
Modeling And Control ◽  
Aerial Manipulator ◽  
Initial Appearance ◽  
Aerial Vehicle ◽  
New Type ◽  
And Control ◽  
Flying Robot

SUMMARYThe aerial manipulator is a special and new type of flying robot composed of a rotorcraft unmanned aerial vehicle (UAV) and a/several manipulator/s. It has gained a lot of attention since its initial appearance in 2010. This is mainly because it enables traditional UAVs to conduct versatile manipulating tasks from air, considerably enriching their applications. In this survey, a complete and systematic review of related research on this topic is conducted. First, various types of structure designs of aerial manipulators are listed out. Subsequently, the modeling and control methods are introduced in detail from the perspective of two types of typical application cases: free-flight and motion-restricted operations. Finally, challenges for future research are presented.

scholarly journals Design and Analysis of Collaborative Unmanned Surface-Aerial Vehicle Cruise Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Man Zhu ◽  
Yuan-Qiao Wen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Command And Control ◽  
Collaborative Model ◽  
Weighting Method ◽  
Unmanned Surface Vehicle ◽  
Control Networks ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
And Control

With the increasing application of unmanned surface vehicle-unmanned aerial vehicles (USV-UAVs) in maritime supervision, research on their deployment and control is becoming vitally important. We investigate the application of USV-UAVs for synergistic cruising and evaluate the effectiveness of the proposed collaborative model. First, we build a collaborative model consisting of the cruise vehicles and communication, detection, and command-and-control networks for the USV-UAV. Second, based on an analysis of the problems faced by collaborative USV-UAV systems, we establish a model to evaluate the effectiveness of such synergistic cruises. Third, we propose a weighting method for each evaluation factor. Finally, a model consisting of one UAV and four USVs is employed to validate our synergistic cruise model.

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