Open Access Open Access  Restricted Access Subscription Access

Design, Kinematic Modeling and Implementation of Integrated Flapping Wing Micro Aerial Vehicle Flight Platform

Abelio Juniar, Beryl Wicaksono, Admira Nuradzhani, Bambang Riyanto Trilaksono, Agoes Moelyadi

Abstract


Advanced technological development of aerial robot, requires the engineers to develop renewable flying mechanism. Flapping wing micro aerial vehicle (MAV) inspired by the flying ability of birds and insects. Electro-mechanical design of flapping wing MAV, kinematic modeling and the integration are successfully implemented. Small and lightweight robot design also successfully implemented to get a platform that can fly and maneuver easily. Crank-shaft mechanism as the flapping mechanism and modelling to achieve particular flap frequency is implemented in this robot. Biplane wing configuration and the tail are designed to obtain a stable platform. Control system of the robot getting feedback from the inertial measurement unit (IMU) sensor. The data is processed by a microprocessor with stabilization algorithm which is then fed to the actuator. Flight test showed that the robot can fly up to 90 seconds in the air with the forward speed up to 4 m/s. Integrated systems of flapping wing MAV is also equipped with a camera and ground control station as a data telemetry center for flight attitude parameters monitoring function and real-time sensing purposes.

Full Text:

PDF

References


Bruggeman, B. (2010). Improving flight performance of Delfly II in hover by improving wing design and driving mechanism. Delft University of Technology.

S. Zhang, C. Zhu, J. K. O. Sin, and P. K. T. Mok, “A novel ultrathin elevated channel low-temperature poly-Si TFT,” IEEE Electron Device Lett., vol. 20, pp. 569–571, Nov. 1999.

Chirarattananon, P., Ma, K., & Wood, R. (2014). Adaptive control of a milimeter-scale flapping-wing robot. Bioinspir. Biomim.

Didel. (t.thn.). Dipetik 12 5, 2014, http://didel.com/microkit/moteurs/Motors.html

K. S. Shigeoka, "Velocity and Altitude Control of an Ornithopter Micro Aerial Vehicle," Department of Electrical and Computer Engineering, The University of Utah, 2007.

InvenSense.Inc, "MPU-6000 and MPU-6050 Register Map and Descriptions Revision 4.0," 03 09 2012. [Online]. Available: https://www.olimex.com/Products/Modules/Sensors/MODMPU6050/resources/RM-MPU-60xxA_rev_4.pdf. [Accessed 15 01 2015].

J.-H. Han, J.-Y. Lee and D.-K. Kim, "Ornithopter Modeling for Flight

Simulation," International Conference on Control, Automation and Systems 2008, 2008.

S.-F. Wu, C. Engelen, Q.-P. Chu, R. Babuska, J. Mulder and G. Ortega,

"Fuzzy Logic Based Attitude Control of the Spacecraft X-38 along Re-Entry Trajectory," Control Engineering Practice 9, 2001.

S. A. Zaheer and J.-H. Kim, "Type-2 Fuzzy Airplane Altitude Control,"

IEEE International Conference on Fuzzy Systems, vol. 11, pp. 2170-2176, 2011.

H. Djojodihardjo, A. S. S. Ramli and S. Wiriadidjaja, "Kinematic and

Aerodynamic Modelling of Flapping Wing Ornithopter," International Conference of Advances Science and Contemporary Engineering, 2012.

B. Remes, P. Esden-Tempski, F. van Tienen, E. Smeur, C. De Wagter

and G. de Croon, "Lisa-S 2.8g autopilot for GPS-based flight of MAVs".

J.-S. R. Jang, Neuro-Fuzzy and Soft Computing, A Computational Approach to Learning and Machine Intelligence, Upper Saddle River: Prentice Hall, 1997.




DOI: http://dx.doi.org/10.21535%2FProICIUS.2015.v11.725

Refbacks

  • There are currently no refbacks.