Abstract:
Flapping wing aerial vehicles are nowadays in demand due to surveillance, civil needs, espionage and border missions.A lot of challenges exists in the development of autonomous
flight missions for the flapping wing aerial vehicles which weigh
less than 2 kg. This research focused on the development of data
driven control system mathematical model and implementation
on flapping wing platform in order to realize the autonomous
flight.In this research,behavior of flapping wing aerial system
is investigated using inertial measurement unit, barometer, GPS
and wireless telemetry. In order to develop the mathematical
model estimation as we utilized the real time telemetry data
by doing flights in the fields.System parameters data was feed
back to ground station with wireless telemetry which would do
processing of the data to develop the mathematical model for the
pitch, roll, yaw and height control behavior. Instead of relying on
the theoretical mathematical models, which often are challenging
to implement due to a lot complex mathematical calculations
involved, system identification approach has been utilized and
practically implemented with successful results.
Index Terms—Mathematical Modeling , Autonomous
Flight,Wireless Sensors, PID Controller, Linear Feedback
Control, Flapping Bird,Ground Control Station.
Authors:
1. Zarrar Haider (Brookfield Villages & UCC, Ireland
)
2. Kashif Ali (PIEAS, Pakistan)
3. Malik Zohaib (EST, Pakistan)
References:
1. Doncieux, S et al. (2006), Building an Artificial Bird: Goals and Accomplishments of the ROBUR Project, European Micro Aerial Vehicles Pesavento, Umberto, and Z. Jane Wang. ”Flapping wing flight can save aerodynamic power compared to steady flight.” Physical review letters
103.11 (2009): 118102.
2. John Gerdes, Alex Holness, Ariel Perez-Rosado, Luke Roberts, Adrian
Greisinger, Eli Barnett, Johannes Kempny, Deepak Lingam, Chen-Haur
Yeh, Hugh A. Bruck, and Satyandra K. Gupta. Robo Raven: A FlappingWing Air Vehicle with Highly Compliant and Independently Controlled
Wings. Soft Robotics.Dec 2014.275-288.
3. Folkertsma, G. A., Straatman, W., Nijenhuis, N., Venner, C. H.,and
Stramigioli, S. (2017). Robird: a robotic bird of prey. IEEE robotics
and automation magazine, 24(3), 22-29.
4. R. Zufferey et al., ”Design of the High-Payload Flapping Wing Robot
E-Flap,” in IEEE Robotics and Automation Letters, vol. 6, no. 2, pp.
3097-3104, April 2021, doi: 10.1109/LRA.2021.3061373.
5. C. Ruiz, J.A. Acosta, A. Ollero, Aerodynamic reduced-order Volterra ´
model of an ornithopter under high-amplitude flapping,Aerospace Science and Technology, Volume 121,2022,107331,ISSN 1270-9638.
6. Yang W, Wang L, Song B. Dove: A biomimetic flapping-wing micro air
vehicle. International Journal of Micro Air Vehicles. 2018;10(1):70-84.
doi:10.1177/1756829317734837.
7. H. R. Vejdani, ”Dynamics and stability of Bat-Scale Flapping Wing Hovering Robot,” 2019 IEEE 15th International Conference on Automation
Science and Engineering (CASE), Vancouver, BC, Canada, 2019, pp.
1106-1111, doi: 10.1109/COASE.2019.8843318.
8. spectrum.ieee.org/video-friday-festos-bionicswift
9. Z. Haider, M. M. Zohaib, F. Haider and E. Shaghaei, ”Mathematical
Modeling and Control System Design of Flapping Wing Unmanned Air
Vehicle,” 2021 4th International Conference on Robotics, Control and
Automation Engineering (RCAE), Wuhan, China, 2021, pp. 224-228,
doi: 10.1109/RCAE53607.2021.9638883.
10. W. He, X. Mu, L. Zhang and Y. Zou, ”Modeling and trajectory tracking
control for flapping-wing micro aerial vehicles,” in IEEE/CAA Journal
of Automatica Sinica, vol. 8, no. 1, pp. 148-156, January 2021, doi:
10.1109/JAS.2020.1003417.
11. Z. Haider, M. M. Zohaib, H. H. Mahmood and M. U. Pirzada, ”Control
System Mathematical Model Design of Ornithopter Flapping Wing Unmanned Air Vehicle for Agile Performance,” 2021 Seventh International
Conference on Aerospace Science and Engineering (ICASE), Islamabad,
Pakistan, 2021, pp. 1-5, doi: 10.1109/ICASE54940.2021.9904128.
12. Wissa A, Grauer J, Guerreiro N, et al. Free Flight Testing and Performance Evaluation of a Passively Morphing Ornithopter. International
Journal of Micro Air Vehicles. 2015;7(1):21-40. doi:10.1260/1756-
8293.7.1.21
13. Jared Grauer, Evan Ulrich, James Hubbard Jr., Darryll Pines
and J. Sean Humbert Testing and System Identification of an
Ornithopter in Longitudinal Flight, Published Online:22 May
2012https://doi.org/10.2514/1.C031208
14. T. Mueller and J. DeLaurier, An Overview of Micro Air Vehicle
Aerodynamics, vol. 195 of Progress in Aeronautics and Astronautics,
chapter 1, pp. 110, Aiaa, 2001.
15. Shu T, Zhang WP, Mou JW ”Research progress on control of bio inspired
flapping-wing micro air vehicles”. Beijing, China. Piscataway: IEEE
Press; 2019. p. 842–7.
16. A Banazadeh, N Taymourtash,”Adaptive attitude and position control
of an insect-like flapping wing air vehicle”,Nonlinear Dynamics 85 (1),
47-66.
17. Shuanghou Deng, Jun Wang, Hanru Liu, Experimental study
of a bio-inspired flapping wing MAV by means of force and
PIV measurements,Aerospace Science and Technology,Volume
94,2019,105382,ISSN 1270-9638.
18. Jiaqing Kou, Weiwei Zhang, Data-driven modeling for unsteady aerodynamics and aeroelasticity, Progress in Aerospace Sciences, Volume
125,2021,100725,ISSN 0376-0421.
Page(s): 44-50
Date of Publication: 19 September 2024