Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33093
Autonomous Flight Performance Improvement of Load-Carrying Unmanned Aerial Vehicles by Active Morphing
Authors: Tugrul Oktay, Mehmet Konar, Mohamed Abdallah Mohamed, Murat Aydin, Firat Sal, Murat Onay, Mustafa Soylak
Abstract:
In this paper, it is aimed to improve autonomous flight performance of a load-carrying (payload: 3 kg and total: 6kg) unmanned aerial vehicle (UAV) through active wing and horizontal tail active morphing and also integrated autopilot system parameters (i.e. P, I, D gains) and UAV parameters (i.e. extension ratios of wing and horizontal tail during flight) design. For this purpose, a loadcarrying UAV (i.e. ZANKA-II) is manufactured in Erciyes University, College of Aviation, Model Aircraft Laboratory is benefited. Optimum values of UAV parameters and autopilot parameters are obtained using a stochastic optimization method. Using this approach autonomous flight performance of UAV is substantially improved and also in some adverse weather conditions an opportunity for safe flight is satisfied. Active morphing and integrated design approach gives confidence, high performance and easy-utility request of UAV users.Keywords: Unmanned aerial vehicles, morphing, autopilots, autonomous performance.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1338744
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2269References:
[1] Austin, R. 2010. Unmanned aircraft systems. Wiley.
[2] Dink, Y., Liu, Y. C., and Hsiao, F. B. The application of extended Kalman filtering to autonomous formation flight of small UAV system. Aircraft Engineering and Aerospace Technology. 1(2), 154-186.
[3] Drak, A., Hejase, M., ElShorbagy, M., Wahyudie, A., & Noura, H. 2014. Autonomous Formation Flight Algorithm and Platform for Quadrotor UAVs. International Journal of Robotics and Mechatronics. 1(4), 124-132.
[4] Luca De Filippis, Giorgio Guglieri, Fulvia B. Quagliotti. 2014. A novel approach for trajectory tracking of UAVs. Aircraft Engineering and Aerospace Technology: An International Journal. 86 (3), 198 – 206.
[5] Hadi, G., Varianto, R., Trilaksono, B., and Budiyono, A. 2014. Autonomous UAV System Development for Payload Dropping Mission. Journal of Instrumentation, Automation, and Systems. 1(2), 72-77.
[6] Grigoriadis, K. M., Carpenter, M. J. Zhu, G., and Skelton, R. E. 1993. Optimal Redesign of Linear Systems. Paper presented at Proceedings of the American Control Conference, San Francisco, CA.
[7] Grigoriadis, K. M., Zhu, G., and Skelton, R. E. 1996. Optimal Redesign of Linear Systems. Journal of Dynamic Systems, Measurement, and Control. 118 (3), 598–605.
[8] Krog, L., Tucker, A., Kemp, M., and Boyd, R. 2004. Topology Optimization of Aircraft Wing Box Ribs. Paper presented at 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Albany, New York, USA.
[9] Park, K., Han, J. W., Lim, H. J., Kim, B. S. and Lee, J. 2008. Optimal Design of Airfoil with High Aspect Ratio in Unmanned Aerial Vehicles. World Academy of Science, Engineering and Technology, 2 (4), 171- 177.
[10] Qun, W. and Hong-quang, J. 2011. Optimal design of UAV’s pod shape. Paper presented at International Symposium on Photoelectronic Detection and Imaging: Advances in Infrared Imaging and Applications Beijing, China.
[11] Moosavian, A., Xi, F., and Hashemi, S. M. 2013. Design and Motion Control of Fully Variable Morphing Wings. Journal of Aircraft. 50(4), 1189-1201.
[12] Yue, T. and Wang, L. 2013. Longitudinal Linear Parameter Varying Modeling and Simulation of Morphing Aircraft. Journal of Aircraft. 50(6), 1673-1681.
[13] Chao, H., Cao, Y., and Chen, Y. Q. 2007. Autopilots for Small Fixed- Wing Unmanned Aerial Vehicles: A Survey. Paper presented at IEEE International Conference on Mechatronics and Automation, Harbin, China.
[14] Jung, D., Ratti, J., Tsiotras, P. 2009. Real-time implementation and validation of a new hierarchical path planning scheme of UAVs via hardware-in-the-loop simulation. Journal of Intelligent and Robotic Systems, 54 (1-3), 163-281.
[15] Sartori, D. 2014. Design, implementation, and testing of advanced control laws for fixed-wing UAVs. PhD dissertation, Politecnico di Torino, Torino, Italy.
[16] Nelson, R. C. 2007. Flight Stability and Automatic Control. 2nd ed., McGraw-Hill, New York, chapters 2-6.
[17] Zagi-The original R/C EPP foam wing homepage (2015), http//:www.zagi.com.
[18] Vural, S. Y. and Hajiyev, C. 2008. Autopilot system design for a small unmanned aerial vehicle. MS thesis, Istanbul Technical University, Istanbul, Turkey.
[19] Vural, S. Y. and Hajiyev, C. 2013. LQR controller with Kalman estimator applied to UAV longitudinal dynamics. Scientific Research Journal. 4, 36-41.
[20] Cardenas, E. M., Boschetti, P. J., and Celi, M. R. 2012. Design of control systems to hold altitude and heading in severe atmospheric disturbances for an unmanned airplane. Paper presented at 50th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition, Nashville, Tennessee.
[21] Jeni, S. D. and Budiyono, A. 2006. Automatic Flight Control System”, Lecture notes for Malaysian Institute of Aviation Technology.
[22] U.S. Military Handbook MIL-HDBK-1797, 1997.
[23] Jang, J. S., Liccardo, D. 2006. Automation of small UAVs using a low cost mems sensor and embedded computing platform.
[24] Sultan, C. 2010. Proportional damping approximation using the energy gain and simultaneous perturbation stochastic approximation. Mechanical Systems and Signal Processing. 24, 2210-2224.
[25] Oktay, T. 2012. Constrained control of complex helicopter models. PhD Dissertation, Virginia Tech.
[26] Oktay, T. and Sultan, C. (2013), “Simultaneous helicopter and controlsystem design,” Journal of Aircraft, Vol. 50, No. 3, pp. 32-47.
[27] Sadegh, P. and Spall, J. C. (1998), “Optimal random perturbations for multivariable stochastic approximation using a simultaneous perturbation gradient approximation”, IEEE Transactions on Automatic Control, 43(10), pp. 1480-1484.
[28] He, Y. and Fu, M. C. (2003), “Convergence of simultaneous perturbation stochastic approximation for non-differentiable optimization”, IEEE Transactions on Aerospace and Electronic Systems, 48 (8), 1459-1463.