Autonomous Loitering Control for a Flapping Wing Miniature Aerial Vehicle With Independent Wing Control

2014 ◽  
Author(s):  
Luke Roberts ◽  
Hugh A. Bruck ◽  
Satyandra K. Gupta
Keyword(s):  
Energy Efficient ◽  
Pid Controller ◽  
Control Algorithm ◽  
Flapping Wing ◽  
Flight Testing ◽  
Response Error ◽  
Aerial Vehicles ◽  
Aerial Vehicle

Flapping wing miniature aerial vehicles (FWMAVs) offer advantages over traditional fixed wing or quadrotor MAV platforms because they are more maneuverable than fixed wing aircraft and are more energy efficient than quadrotors, while being quieter than both. Currently, autonomy in FWMAVs has only been implemented in flapping vehicles without independent wing control, limiting their level of control. We have developed Robo Raven IV, a FWMAV platform with independently controllable wings and an actuated tail controlled by an onboard autopilot system. In this paper, we present the details of Robo Raven IV platform along with a control algorithm that uses a GPS, gyroscope, compass, and custom PID controller to autonomously loiter about a predefined point. We show through simulation that this system has the ability to loiter in a 50 meter radius around a predefined location through the manipulation of the wings and tail. A simulation of the algorithm using characterized GPS and tail response error via a PID controller is also developed. Flight testing of Robo Raven IV demonstrated the success of this platform, even in winds of up to 10 mph.

scholarly journals A wireless radiofrequency-powered insect-scale flapping-wing aerial vehicle

2021 ◽  
Vol 4 (11) ◽  
pp. 845-852
Author(s):  
Takashi Ozaki ◽  
Norikazu Ohta ◽  
Tomohiko Jimbo ◽  
Kanae Hamaguchi
Keyword(s):  
Electromagnetic Waves ◽  
Power Transmission ◽  
Flapping Wing ◽  
Micro Aerial Vehicles ◽  
Wireless Power ◽  
Lithium Polymer Batteries ◽  
Confined Spaces ◽  
Weight Density ◽  
Aerial Vehicles ◽  
Aerial Vehicle

AbstractInsect-scale aerial vehicles are useful tools for communication, environmental sensing and surveying confined spaces. However, the lack of lightweight high-power-density batteries has limited the untethered flight durations of these micro aerial vehicles. Wireless power transmission using radiofrequency electromagnetic waves could potentially offer transmissivity through obstacles, wave-targeting/focusing capabilities and non-mechanical steering of the vehicles via phased-array antennas. But the use of radiofrequency power transmission has so far been limited to larger vehicles. Here we show that a wireless radiofrequency power supply can be used to drive an insect-scale flapping-wing aerial vehicle. We use a sub-gram radiofrequency power receiver with a power-to-weight density of 4,900 W kg–1, which is five times higher than that of off-the-shelf lithium polymer batteries of similar mass. With this system, we demonstrate the untethered take off of the flapping-wing micro aerial vehicle. Our RF-powered aircraft has a mass of 1.8 g and is more than 25 times lighter than previous radiofrequency-powered micro aerial vehicles.

Dynamic Modeling for a Miniature Six-Rotor Unmanned Aerial Vehicle

2013 ◽  
Vol 321-324 ◽  
pp. 819-823 ◽  
Author(s):  
Qi Dong Ma ◽  
Zhen Guo Sun ◽  
Jing Ran Wu ◽  
Wen Zeng Zhang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Driving Force ◽  
Pid Controller ◽  
Control Algorithm ◽  
Driving Forces ◽  
Euler Angles ◽  
Unstable System ◽  
Nonlinear Dynamic Model ◽  
Aerial Vehicle ◽  
Simulation Results

A nonlinear dynamic model of a miniature Six-Rotor is presented. A 4 channels PID controller is designed to operate the under actuated and dynamically unstable system with 6 inputs. Driving forces of 6 rotors are divided into four components such as throttle, roll, pitch and yaw. The control algorithm is simulated with Design Optimization Toolbox in Matlab. After observing the corresponding responses of Euler angles, the altitude and the driving force for each motor, the simulation results show good performance.

Altitude consensus based 3D flocking control for fixed-wing unmanned aerial vehicle swarm trajectory tracking

2016 ◽  
Vol 230 (14) ◽  
pp. 2628-2638 ◽  
Author(s):  
Xiangyin Zhang ◽  
Haibin Duan
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Control Algorithm ◽  
Field Method ◽  
External Input ◽  
Consensus Algorithm ◽  
Aerial Vehicles ◽  
Input Signals ◽  
Aerial Vehicle ◽  
Distributed Tracking

This paper studies the 3D flocking control problem for unmanned aerial vehicle swarm when tracking a desired trajectory. In order to allow the unmanned aerial vehicle swarm to form the stable flocking geometry on a same horizontal plane, the altitude consensus algorithm is applied to the unmanned aerial vehicle altitude control channel, using the trajectory altitude as the external input signals. The flocking control algorithm is only performed in the horizontal channel to control the horizontal position of unmanned aerial vehicles. The distributed tracking algorithm, which controls the local averages of position and velocity of each unmanned aerial vehicle, is implemented to achieve the better tracking performance. The improved artificial potential field method is introduced to achieve the smooth trajectory when avoiding obstacles. The practical dynamic and constraints of unmanned aerial vehicles are also taken into account. Numerical simulations are performed to test the performance of the proposed control algorithm.

Using a Large 2 Degree of Freedom Tail for Autonomous Aerobatics on a Flapping Wing Unmanned Aerial Vehicle

2016 ◽  
Author(s):  
Luke Roberts ◽  
Hugh Bruck ◽  
S. K. Gupta
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Flight Control ◽  
Flapping Wing ◽  
Degree Of Freedom ◽  
Simple Method ◽  
Orientation Change ◽  
Aerial Vehicles ◽  
Angular Velocities ◽  
Aerial Vehicle ◽  
Rotary Wing

Flapping wing unmanned aerial vehicles (FWUAVs) provide an alternative to traditional platforms because they are more maneuverable than fixed wing platforms while being faster, quieter, and more natural looking than rotary wing platforms. While real birds are able to execute complex and highly controlled aerobatic maneuvers, executing FWUAV aerobatics presents unique challenges due to difficulty in execution of controlled quick orientation change. This paper demonstrates a simple method for using a large 2 degree of freedom tail for quick orientation changes and flight control, enabling execution of a pre-programmed backflip maneuver on the Robo Raven V, a hybrid FWUAV. The platform reached angular velocities of up to 420° per second during the maneuver.

scholarly journals Simulation of quadcopter flight altitude stabilization system

2020 ◽  
Vol 33 (02) ◽  
pp. 638-650
Author(s):  
Mikhail Yu. Babich ◽  
Mikhail M. Butaev ◽  
Dmitry V. Pashchenko ◽  
Alexey I. Martyshkin ◽  
Dmitry A. Trokoz
Keyword(s):  
Mathematical Model ◽  
Unmanned Aerial Vehicles ◽  
Control Algorithm ◽  
Angular Position ◽  
The Other ◽  
Practical Implementation ◽  
Stabilization System ◽  
Flight Altitude ◽  
Aerial Vehicles ◽  
Aerial Vehicle

Recently, unmanned aerial vehicles have been an important part of scientific research in various fields. Quadrocopter is an unmanned aerial vehicle with four rotors, two of which rotate clockwise, the other two counterclockwise. Changing the speed of screw rotation allows you to control the movement of the apparatus. The article proposed and tested a mathematical model of a quadcopter. They presented the development of a simple control algorithm that allows to stabilize the height and angular position. The research results show the efficiency of the algorithm and the possibility of its practical implementation. The developed mathematical model can be used instead of a real quadcopter, which will significantly reduce the time during research, as well as avoid the quadrocopter damage, reducing the number of launches.

A distributed swarm control for an agricultural multiple unmanned aerial vehicle system

2019 ◽  
Vol 233 (10) ◽  
pp. 1298-1308 ◽  
Author(s):  
Chanyoung Ju ◽  
Hyoung Il Son
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Control Algorithm ◽  
Haptic Feedback ◽  
Vehicle Control ◽  
Haptic Device ◽  
Aerial Vehicles ◽  
Vehicle System ◽  
Aerial Vehicle ◽  
Control Layer

In this study, we propose a distributed swarm control algorithm for an agricultural multiple unmanned aerial vehicle system that enables a single operator to remotely control a multi-unmanned aerial vehicle system. The system has two control layers that consist of a teleoperation layer through which the operator inputs teleoperation commands via a haptic device and an unmanned aerial vehicle control layer through which the motion of unmanned aerial vehicles is controlled by a distributed swarm control algorithm. In the teleoperation layer, the operator controls the desired velocity of the unmanned aerial vehicle by manipulating the haptic device and simultaneously receives the haptic feedback. In the unmanned aerial vehicle control layer, the distributed swarm control consists of the following three control inputs: (1) velocity control of the unmanned aerial vehicle by a teleoperation command, (2) formation control to obtain the desired formation, and (3) collision avoidance control to avoid obstacles. The three controls are input to each unmanned aerial vehicle for the distributed system. The proposed algorithm is implemented in the dynamic simulator using robot operating system and Gazebo, and experimental results using four quadrotor-type unmanned aerial vehicles are presented to evaluate and verify the algorithm.

scholarly journals Analysis of resonant propulsion flapping wing micro aerial vehicle

2020 ◽  
pp. 327-345
Author(s):  
Kun Feng ◽  
Krzysztof Sibilski
Keyword(s):  
Mathematical Models ◽  
Insect Flight ◽  
Flapping Wing ◽  
Micro Aerial Vehicles ◽  
Micro Aerial Vehicle ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Resonant Property

This article is concerned with the resonant property which is exhibited in insect flight, and analyzes how resonant propulsion works when implemented in powering a flapping wing micro aerial vehicle. This article is divided into three parts. In the first part, information regarding to insect flight, the resonant property, and flapping wing micro aerial vehicles are described. In the second part, mathematical models representing the micro aerial vehicle (basing on the model developed by Bolsman) are applied, simplified and built into simulation in MATLAB. Some interesting properties from the simulations are presented.

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