Integral adaptive autopilot for an unmanned aerial vehicle
Abstract
The aim of research is to study the modern algorithms used in autopilots of unmanned aerial vehicles and formulation of the problem of development and usage of new intellectual methods for automatic control systems. The approach considered in the article is based on the theory of high-precision remote control of dynamic objects and on the complex interaction of methods of theory of invariance, adaptive control and intellectualization of processes of UAV control. One of the features of the proposed method of intellectual control for unmanned aerial vehicle autopilot is the procedure of transforming a multi-dimensional system into an aggregate of virtual autonomous processes, for each of which the control algorithm is easily generated by an autonomous subsystem. Coming up next is the procedure of coordination of actions of all the autonomous systems into single functioning complex. This provides an opportunity to improved precision and sustainability of control. Using the method described in the article allows creating integral and adaptive autopilots to perform complicated spatial maneuvering an unmanned aerial vehicle being based on usage of full non-linear models without simplifications and linearization.
Keyword : unmanned aerial vehicle, control system, invariance, virtual control, autopilot, method, adaptation
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Calise, A., & Rysdyk, R. (1998). Nonlinear adaptive flight control using neural networks. Control Systems Magazine, 18(6), 14-25.
Chao, H., Cao, Y., & Chen, Y. Q. (2010). Autopilots for small unmanned aerial vehicles: a survey. International Journal of Control, Automation, and Systems, 8(1), 36-44. https://doi.org/10.1007/s12555-010-0105-z
Fahlstrom, P., & Gleason, T. (2012). Introduction to UAV systems (4th ed.). New York: Wiley. https://doi.org/10.1002/9781118396780
Feng, G. (2006). A survey on analysis and design of model-based fuzzy control systems. IEEE Transactions on Fuzzy Systems, 14(5), 676-697. https://doi.org/10.1109/TFUZZ.2006.883415
Grytsenko, V., Volkov, O., Komar, М., & Bogachuk, Y. (2018). Intelektualizatsiya suchasnykh system avtomatychnoho keruvannya bezpilotnymy lital᾽nymy aparatamy. Cybernetics and Computer Engineering Journal, 1(191), 45-59.
Johnson, E. N., & Kannan, S. K. (2002, August). Adaptive flight control for an autonomous unmanned helicopter. Paper presented at the AIAA Guidance, Navigation, and Control Conference and Exhibit, Monterey, California (No. AIAA-2002-4439).
Kharchenko, V., Chepizhenko, V., Tunik, A., & Pavlova, S. (2012). Avionika bezpilotnykh lital᾽nykh aparativ. Kiev: TOV Abrys-prynt.
Kumon, M., Udo, Y., Michihira, H., Nagata, M., Mizumoto, I., & Iwai, Z. (2006). Autopilot system for Kiteplane. IEEE/ASME Transactions on Mechatronics, 11(5), 615-624. https://doi.org/10.1109/TMECH.2006.882994
Lopez, J., Dormido, R., Dormido, S., & Gomez, J. P. (2015). A robust controller for an UAV flight control system. The Scientific World Journal, 2015. Articale ID 403236. https://doi.org/10.1155/2015/403236
Lopez, J., Dormido, R., Gomez, J. P., Dormido, S., & Diaz, J. M. (2007, July 2-5). Comparison of H-infinity with QFT applied to an Altitude Command Tracker for an UAV. Paper presented at the Proceedings of the European Control Conference, Kos, Greece.
Moiseyev, V. S. (2013). Prikladnaya teoriya upravleniya bespilotnymi letatel᾽nymi apparatami: monografiya. Kazan: GBU Respublikanskiy tsentr monitoringa kachestva obrazovaniya.
Pavlov, V., & Pavlova, S. (2015). Intellektual᾽noye upravleniye slozhnymi nelineynymi dinamicheskimi sistemami. Kiev: Naukova dumka.
Ross, T. J. (2004). Fuzzy logic with engineering applications (2nd ed.). New York: Wiley.
Shilov, K. (2014). Razrabotka sistemy avtomaticheskogo upravleniya bespilotnym letatel᾽nym apparatom mul᾽irotornogo tipa. Trudy MFTI, 4, 139-152.