Flight Control of TUAV with Coaxial Rotor and Ducted Fan Configuration by NARMA-L2 Controllers for Enhanced Situational Awareness

Authors: Igor Astrov, Andrus Pedai, Boris Gordon

Abstract:

This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for tactical unmanned aerial vehicle (TUAV). With the SA strategy, we proposed a two stage flight control procedure using two autonomous control subsystems to address the dynamics variation and performance requirement difference in initial and final stages of flight trajectory for an unmanned helicopter model with coaxial rotor and ducted fan configuration. This control strategy for chosen model of TUAV has been verified by simulation of hovering maneuvers using software package Simulink and demonstrated good performance for fast stabilization of engines in hovering, consequently, fast SA with economy in energy can be asserted during search-and-rescue operations.

Keywords: Coaxial rotors, ducted fan, NARMA-L2 neurocontroller, situational awareness, tactical unmanned aerial vehicle.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1334856

References:

[1] M. R. Ensleyi "Toward a theory of wituation awareness in dynamic systems," Human Factors, vol. 37, pp. 32-64, March 1995.
[2] J. Gorman, N. Cooke, and J. Winner, "Measuring team situation awareness in decentralized command and control environments," Ergonomics, vol. 49, pp. 1312-1325, October 2006.
[3] Interim Brigade Combat Team Newsletter. (Online). Available: http://www.globalsecurity.org/military/library/ report/call/call_01-18_ toc.htm
[4] S. D. Prior, S. T. Shen, A. S. White, S. Odedra, M. Karamanoglu, M. A. Erbil, and T. Foran, "Development of a novel platform for greater situational awareness in the urban military terrain", in Proc. 8th International Conf. Engineering Psychology and Cognitive Ergonomics, San Diego, USA, 2009, pp. 120-125.
[5] I. Astrov and A. Pedai, "Control of hovering manoeuvres in unmanned helicopter for enhanced situational awareness," in Proc. International Conf. Industrial Mechatronics and Automation, Chengdu, China, 2009, pp. 143-146.
[6] S. Shouzhao, A. A. Mian, Z. Chao, and J. Bin, "Autonomous takeoff and landing control for a prototype unmanned helicopter," Control Engineering Practice, vol. 18, pp. 1053-1059, September 2010.
[7] K. S. Narendra and S. Mukhopadhyay, "Adaptive control using neural networks and approximate models," IEEE Trans. Neural Networks, vol. 8, pp. 475-485, May 1997.