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Design of formation control laws for manoeuvred flight

Published online by Cambridge University Press:  12 October 2016

G. Campa
Affiliation:
Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, USA
S. Wan
Affiliation:
Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, USA
M. R. Napolitano
Affiliation:
Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, USA
B. Seanor
Affiliation:
Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, USA
M. L. Fravolini
Affiliation:
Department of Electronic and Information EngineeringPerugia University, Perugia, Italy

Abstract

This paper presents identification, control synthesis and simulation results for an YF-22 aircraft model designed, built, and instrumented at West Virginia University. The ultimate goal of the project is the experimental demonstration of formation flight for a set of 3 of the above models. In the planned flight configuration, a pilot on the ground maintains controls of the leader aircraft while a wingman aircraft is required to maintain a pre-defined position and orientation with respect to the leader. The identification of both a linear model and a nonlinear model of the aircraft from flight data is discussed first. Then, the design of the control scheme is presented and discussed with an emphasis on the amount of information, relative to the leader aircraft, needed by the wingman to maintain formation. Using the developed nonlinear model, the control laws for a maneuvered flight of the formation are then simulated with Simulink® and displayed with the Virtual Reality Toolbox®. Simulation studies have been performed to evaluate the effects of specific parameters and the system robustness to atmospheric turbulence. The conclusions from this analysis have allowed the formulation of specific guidelines for the design of the electronic payload for formation flight.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 2004 

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References

1. Blake, W. and Multhopp, D. Design, performance, and modeling considerations for close formation flight, Proceedings of the 1999 AIAA GNC Conference, AIAA paper 1999-4343, Portland, OR, August 1999.Google Scholar
2. Pachter, M., D’Azzo, J.J. and Proud, A.W. Tight formation flight control, J Guidance, Control, and Dynamics, March-April 2001, 24, (2), pp 246254.Google Scholar
3. Giulietti, F., Pollini, L. and Innocenti, M. Autonomous formation flight, IEEE Control Systems Magazine, 2000, 20, (6), pp 3444.Google Scholar
4. Proud, A.W. Close Formation Flight Control, MS Thesis, AFIT/GE/ENG/99M-24, School of Engineering, Air Force Institute of Technology (AU), Wright-Patterson AFB, OH, March 1999.Google Scholar
5. Hall, J.K. Three Dimensional Formation Flight Control, MS Thesis, AFIT/GE/ENG/00M-06, School of Engineering, Air Force Institute of Technology (AU), Wright-Patterson AFB, OH, March 2000.Google Scholar
6. Pachter, M., D’Azzo, J.J. and Dargan, J.L. Automatic formation flight control, J Guidance, Control, and Dynamics, 1994, 17, (6), pp 13801383.Google Scholar
7. Giulietti, F., Pollini, L. and Innocenti, M. Formation flight control: A behavioral approach, Proceedings of the 2001 AIAA GNC Conference, AIAA Paper 2001-4239, Montreal, Canada, August 2001.Google Scholar
8. Binetti, P., Ariyur, K.B., Krstic, M. and Bernelli, F. Control of formation flight via extremum seeking, Proceedings of the 2002 America Control Conference, Anchorage, AK, May 2002.Google Scholar
9. Schumacher, C.J. and Kumar, R. Adaptive control of UAVs in close-coupled formation flight, Proceedings of the 2000 American Control Conference, Chicago, IL, June 2000.Google Scholar
10. Schumacher, C.J. AND Singh, S.N. Non linear control of multiple UAVs in closecoupled formation flight, Proceedings of the 2000 AIAA GNC Conference, AIAA paper 2000-4373, Denver, CO, August 2000.Google Scholar
11. Singh, S.N., Pachter, M., Chandler, P., Banda, S., Rasmussen, S. and Schumacher, C.J. Input-output invertibility and sliding mode control for close formation flying of multiple UAVs, Proceedings of the 2000 AIAA GNC Conference, Denver, CO, August 2000.Google Scholar
12. Calise, A.J. and Rysdyk, R.T. Nonlinear adaptive flight control using neural networks, IEEE Control Systems Magazine, 1998, 18, (6).Google Scholar
13. Ray, R.J., Cobleigh, B., Vachon, M.J., and St John, C. Flight test techniques used to evaluate performance benefits during formation flight, Proceedings of the 2002 AIAA GNC Conference, AIAA paper 2002-4492, Monterey, CA, August 2002.Google Scholar
14. Hansen, J.L. and Cobleigh, B.R. Induced moment effects of formation flight using two F/A-18 aircraft, Proceedings of the 2002 AIAA GNC Conference, AIAA paper 2002-4489, Monterey, CA, August 2002.Google Scholar
15. Vachon, M.J., Ray, R.J., Walsh, K.R. and Ennix, K. F/A-18 aircraft performance benefits measured during the autonomous formation flight project, Proceedings of the 2002 AIAA GNC Conference, AIAA paper 2002-4491, Monterey, CA, August 2002.Google Scholar
16. Misovec, K. Applied adaptive techniques for F/A-18 formation flight, Proceedings of the 2002 AIAA GNC Conference, AIAA paper 2002-4550, Monterey, CA, August 2002.Google Scholar
17. Lavretsky, E. F/A-18 Autonomous formation flight control system design, Proceedings of the 2002 AIAA GNC Conference, AIAA Paper 2002-4757, Monterey, CA, August 2002.Google Scholar
18. Hanson, C.E., Ryan, J., Allen, M.J. and Jacobson, S.R. An overview of flight test results for a formation flight autopilot, Proceedings of the 2002 AIAA GNC Conference, AIAA paper 2002-4755, Monterey, CA, August 2002.Google Scholar
19. Ljung, L. System Identification: Theory for the User, 2nd Ed, PTR Prentice Hall, Upper Saddle River, Englewood Cliffs, NJ, 1999.Google Scholar
20. Overschee, Van, De Moor, B. Subspace Identification for Linear Systems: Theory, Implementation, Applications. Kluwer Academic Publishers, 1996.Google Scholar
21. Stengel, R.F. Optimal control and estimation,Dover Publication, New York, 1994.Google Scholar
22. Dobson, A.J. An Introduction to Generalized Linear Models, 1990, CRC Press.Google Scholar
23. Napolitano, M.R., West Virginia University, Air Force Office of Scientific Research (AFOSR) Grant F49620-98-1-0136 Final Report, March 2002.Google Scholar
24. Maine, R.E. and Iliff, K.W. Identification of dynamic systems: theory and formulation, NASA RF 1168, June 1986.Google Scholar
25. Stevens, B. and Lewis, F. Aircraft Control and Simulation, John Wiley & Sons, NY, 1992.Google Scholar
26. Campa, G, ‘Airlib’, (February 2003), http://www.mathworks.com/matlabcentral/fileexchange/ Google Scholar
27. Hock, W. and Schittowski, K. A Comparative performance evaluation of 27 nonlinear programming codes, Computing, 1983, 30, p 335.Google Scholar
28. Giulietti, F., Napolitano, M.R., Capetta, R. and Innocenti, M. The complete aircraft model within a formation flight, Proceedings of the 2002 AIAA Atmospheric Flight Mechanics Conference, August 2002 Google Scholar
29. The VRML Web Repository (December. 2002): http://www.web3d.org/vrml/vrml.htm Google Scholar