scholarly journals In-flight data acquisition and flight testing for system identification of flapping-wing MAVs

2017 ◽  
Author(s):  
J.V. Caetano ◽  
S. F. Armanini ◽  
M. Karasek
Keyword(s):  
System Identification ◽  
Data Acquisition ◽  
Flapping Wing ◽  
Flight Testing ◽  
Flight Data

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 Flight manoeuvring and safe flight visualization with the aid of wide-ranging scrutiny and automation software

2019 ◽  
Vol 272 ◽  
pp. 01021
Author(s):  
J V Muruga Lal Jeyan ◽  
Jency Lal ◽  
M Senthil Kumar ◽  
Arfaj Ahamed Anwar
Keyword(s):  
Data Acquisition ◽  
Data Acquisition System ◽  
Acquisition System ◽  
Display Module ◽  
Flight Data ◽  
Difficult Time ◽  
Standard Procedures ◽  
2D And 3D ◽  
The Impact ◽  
Graphical Presentation

This document guides to an efficient use of FDVCAS system. FDVCAS is a reconstruction, playback, interactive visualization tool, which collects, stores, processes, analyses and present the flight data in high fidelity graphical presentation in 2D and 3D format. It synchronizes and presents in both graphical and synthetic visual form to the extends of analysing the impact of the data on the system in 3D graphic animation. The existing process involves in capturing the data from different input sources and formats, analysing the features of the data monitoring is done manually in offline in a unsynchronized fashion, This is difficult, time consuming and requires highly skilled technical expertise as it is visualized in plain data form. The above standard procedures followed shall be integrated and automated with minimum intelligence to be built, in with the system. In order to analyse the flight data in a coherent way it is required to integrate both 2D and 3D form The proposed concept is the Development of a system with a single solution by providing data display, graphical charts and replay features with a sophisticated graphical user interface, which is super imposed on the outside window imagery. FDVCAS consists of Bypass data acquisition system, Outside Window Imagery (OWI) system with graphical analyser. Bypass data acquisition system receives data from aircraft recorder and transmits the data in engineering format to FDVCAS system. The OWI system has three main modules namely, 3D Visual module, GUI based Graphical analyser and Warning display module. The warnings and the graphical plots are super imposed on the 3D Visual.

Initial design of flight data acquisition unit (FDAU)

2020 ◽  
Author(s):  
Try Kusuma Wardana ◽  
Fuad Surastyo Pranoto ◽  
Sayr Bahri ◽  
Prasetyo Ardi Probo Suseno ◽  
Atik Bintoro
Keyword(s):  
Data Acquisition ◽  
Flight Data ◽  
Initial Design ◽  
Data Acquisition Unit

scholarly journals Improving Prediction of Flapping-Wing Motion By Incorporating Actuator Constraints With Models of Aerodynamic Loads Using In-Flight Data

2017 ◽  
Vol 9 (2) ◽  
Author(s):  
John W. Gerdes ◽  
Hugh A. Bruck ◽  
Satyandra K. Gupta
Keyword(s):  
Experimental Data ◽  
Design Space Exploration ◽  
Experimental Testing ◽  
Flapping Wing ◽  
Modeling Framework ◽  
Flight Data ◽  
Flexible Wing ◽  
Wing Motion ◽  
Aerodynamic Model ◽  
Strip Theory

Flapping-wing flight is a challenging system integration problem for designers due to tight coupling between propulsion and flexible wing subsystems with variable kinematics. High fidelity models that capture all the subsystem interactions are computationally expensive and too complex for design space exploration and optimization studies. A combination of simplified modeling and validation with experimental data offers a more tractable approach to system design and integration, which maintains acceptable accuracy. However, experimental data on flapping-wing aerial vehicles which are collected in a static laboratory test or a wind tunnel test are limited because of the rigid mounting of the vehicle, which alters the natural body response to flapping forces generated. In this study, a flapping-wing aerial vehicle is instrumented to provide in-flight data collection that is unhindered by rigid mounting strategies. The sensor suite includes measurements of attitude, heading, altitude, airspeed, position, wing angle, and voltage and current supplied to the drive motors. This in-flight data are used to setup a modified strip theory aerodynamic model with physically realistic flight conditions. A coupled model that predicts wing motions is then constructed by combining the aerodynamic model with a model of flexible wing twist dynamics and enforcing motor torque and speed bandwidth constraints. Finally, the results of experimental testing are compared to the coupled modeling framework to establish the effectiveness of the proposed approach for improving predictive accuracy by reducing errors in wing motion specification.

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