×

A nonlinear dynamic inversion-based neurocontroller for unmanned combat aerial vehicles during aerial refuelling. (English) Zbl 1293.93555

Summary: The paper presents the development of modelling and control strategies for a six-degree-of-freedom, Unmanned Combat Aerial Vehicle (UCAV) with the inclusion of the center of gravity position travel during the straight-leg part of an in-flight refuelling manoeuvre. The centre of gravity position travel is found to have a parabolic variation with an increasing mass of aircraft. A nonlinear dynamic inversion-based neurocontroller is designed for the process under investigation. Three radial basis function neural networks are exploited in order to invert the dynamics of the system, one for each control channel. Modal and time-domain analysis results show that the dynamic properties of the aircraft are strongly influenced during aerial refuelling. The effectiveness of the proposed control law is demonstrated through the use of simulation results for an F-16 aircraft. The longitudinal neurocontroller provides interesting results, and performs better than a baseline nonlinear dynamic inversion controller without neural network. On the other hand, the lateral-directional nonlinear dynamic inversion-based neurocontroller did not perform well as the longitudinal controller. It is concluded that the nonlinear dynamic inversion-based neurocontroller could be applied to control an unmanned combat aerial vehicle during aerial refuelling.

MSC:

93C85 Automated systems (robots, etc.) in control theory
92B20 Neural networks for/in biological studies, artificial life and related topics
93C10 Nonlinear systems in control theory
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Bajodah, A.H. (2009). Generalised dynamic inversion spacecraft control design methodologies, IET Control Theory and Applications3(2): 239-251.
[2] Battipede, M., Napolitano, P., Perhinschi, M.G., Massotti, L. and Lando, M. (2003). Implementation of an adaptive predictor-corrector neural controller within the NASA IFCS F-15 WVU simulator, Proceedings of the AmericanControl Conference, Denver, CO, USA, pp. 1302-1307.
[3] Bishop, C.M. (1995). Neural Networks for Pattern Recognition, Oxford University Press, Oxford. · Zbl 0868.68096
[4] Clark, R.M. (2000). Uninhabited Combat Vehicles: Airpowerby the People, For the People, But Not with the People, Air University Press, Maxwell Air Force Base, AL.
[5] Dell’Aquila, R.V., Napolitano, M.R. and Mammarella, M. (2007). Realtime machine-vision-based position sensing system for UAV aerial refueling, Journal of Real-Time ImageProcessing 1(3): 213-224.
[6] Deng, J., Becerra, V.M. and Stobart, R. (2009). Input constraints handling in an MPC/feedback linearization scheme, International Journal of Applied Mathematicsand Computer Science 19(2): 219-232, DOI: 10.2478/v10006-009-0018-2. · Zbl 1167.93336 · doi:10.2478/v10006-009-0018-2
[7] Dogan, A. and Kim, E. (2007). Control and simulation of relative motion for aerial refueling in racetrack manoeuvres, Journal of Guidance, Control and Dynamics30(5): 1551-1557.
[8] Dogan, A., Sato, S. and Blake, W. (2005). Flight control and simulation for aerial refuelling, Proceedings of the AIAAGuidance, Navigation and Control Conference and Exhibit,San Francisco, CA, USA, Paper 2005-6264, pp. 1-15.
[9] Dufrene, W.R. (2004). AI techniques in uninhabited aerial vehicle flight, IEEE Aerospace and Electronic SystemsMagazine 19(8): 8-12.
[10] Elliot, C.M. and Dogan, A. (2010). Investigating nonlinear control architecture options for aerial refueling, Proceedingsof the AIAA Atmospheric Flight Mechanics Conference,Toronto, Canada, Paper 2010-7927.
[11] Eshel, T. (2004). Extending the F-16 range, Defense update, International Online Defense Magazine 1, products/f/f-16-fuel.html.
[12] Etkin, B. and Reid, L.D. (1996). Dynamics of Flight: Stabilityand Control, John Wiley and Sons Inc., New York, NY.
[13] Fravolini, M.L., Ficola, A., Napolitano, M.R., Campa, G. and Perhinschi, M. G. (2003). Development of modelling and control tools for aerial refuelling for UAVs, Proceedings ofthe AIAA Guidance, Navigation and Control Conferenceand Exhibit, TX, USA, Paper 2003-5798.
[14] Gili, A.P. and Battipede, M. (2001). Adaptive neurocontroller for a nonlinear combat aircraft model, Journal of Guidance,Control and Dynamics 24(5): 910-917.
[15] Hagan, M.T. and Demuth, H.B. (1999). Neural networks for control, Proceedings of the American Control Conference,San Diego, CA, USA, pp. 1642-1656.
[16] Hansen, J., Murray, J.E. and Campos, N.V. (2004). The NASA Dryden AAR project: A flight test approach to an aerial refueling system, Proceedings of the AIAA AtmosphericFlight Mechanics Conference, Providence, RI, USA, Paper 2004-4939.
[17] Haykin, S. (1999). Neural Networks. A Comprehensive Foundation, 2nd Edn., Prentice-Hall, Englewood Cliffs, NJ. · Zbl 0934.68076
[18] Ito, D., Georgie, J., Valasek, J. and Ward, D.T. (2002). Reentry vehicle flight controls design guidelines: Dynamic inversion, Technical report, NASA Technical Paper NASA/TP 2002-210771, Flight Simulation Laboratory, Huston, TX.
[19] Jin, Z., Shima, T. and Schumacher, C.J. (2006). Optimal scheduling for refuelling multiple autonomous aerial vehicles, IEEE Transactions on Robots 22(4): 682-693.
[20] Kamalasadan, S. and Ghandakly, A.A. (2011). A neural network parallel adaptive controller for fighter aircraft pitch-rate tracking, IEEE Transactions on Instrumentation and Measurement60(1): 258-267.
[21] Kaneshige, J.T., Bull, J. and Totah, J.J. (2000). Generic neural flight control and autopilot system, Proceedings ofthe AIAA Guidance, Navigation, and Control Conference,Denver, CO, USA, Paper 2000-4281.
[22] Khanafseh, S.M. and Pervan, B. (2007). Autonomous airborne aerial refueling of unmanned air vehicles using the global position system, Journal of Aircraft 44(5): 1670-1682. · doi:10.2514/1.28195
[23] Koch, A. (2005). How to aerial refuel the F-16, htm/refuel.html.
[24] Kung, C.-C. (2008). Nonlinear H\infty robust control applied to F-16 aircraft with mass uncertainty using control surface inverse algorithm, Journal of the Franklin Institute345(6): 851-876. · Zbl 1201.93037 · doi:10.1016/j.jfranklin.2008.05.002
[25] Lane, S.H. and Stengel, R.F. (1988). Flight control design using non-linear inverse dynamics, Automatica 24(4): 471-483. · Zbl 0649.93051 · doi:10.1016/0005-1098(88)90092-1
[26] Lee, S., Ha, C. and Kim, B.S. (2005). Adaptive nonlinear control system design for helicopter robust command augmentation, Aerospace Science and Technology9(3): 241-251. · Zbl 1195.93058 · doi:10.1016/j.ast.2004.12.007
[27] Li, Y., Sundararajan, N. and Saratchandran, P. (2001).
[28] Neuro-controller design for nonlinear fighter aircraft manoeuvre using fully tuned RBF networks, Automatica37(8): 1293-1301. · Zbl 0997.93077 · doi:10.1016/S0005-1098(01)00090-5
[29] Lombaerts, T.J.J., Chu, Q.P., Mulder, J.A. and Joosten, D.A. (2011). Modular flight control for reconfiguration design and simulation, Control Engineering Practice19(6): 540-554. · doi:10.1016/j.conengprac.2010.12.008
[30] MacKunis, W., Patre, P.M., Kaiser, M.K. and Dixon, W.E. (2010). Asymptotic tracking for aircraft via robust and adaptive dynamic inversion methods, IEEE Transactionson Control Systems Technology 18(6): 1448-1456.
[31] Mammarella, M., Campa, G., Napolitano, M.R. and Fravolini, M.L. (2008). Comparison of point matching algorithms for the UAV aerial refueling problem, Machine Vision andApplications 1(3): 213-224.
[32] Mao, W. and Eke, F.O. (2008). A survey of the dynamics and control of aircraft during aerial refueling, Nonlinear Dynamicsand Systems Theory 8(4): 375-388. · Zbl 1159.93347
[33] McFarland, M.B. and Calise, A.J. (2000). Adaptive nonlinear control of agile antiair missiles using neural networks, IEEE Transactions on Control Systems Technology8(5): 749-756.
[34] McLean, D. (1990). Automatic Flight Control Systems, Prentice Hall, New York, NY. · Zbl 0748.93001
[35] Morelli, E.A. (1998). Global nonlinear parametric modeling with application to F-16 aerodynamics, Technical report, Dynamics and Control Branch, NASA Langley Research Centre, Hampton, VA.
[36] Nabney, I.T. (2002). NETLAB: Algorithms for Pattern Recognition, Springer, London. · Zbl 1011.68116
[37] Ochi, Y. and Kominami, T. (2005). Flight control for automatic aerial refuelling via PNG and LOS angle control, Proceedingsof the AIAA Guidance, Navigation and ControlConference and Exhibit, San Francisco, CA, USA, Paper 2005-6268, pp. 1-11.
[38] Ollero, A. and Merino, L. (2004). Control and perception techniques for aerial robotics, Annual Reviews in Control28(2): 167-178. · doi:10.1016/j.arcontrol.2004.05.003
[39] Pachter, M., Houpis, H. and Trosen, D.W. (1997). Design of an air-to-air automatic refueling flight control system using quantitative feedback theory, International Journal of Robustand Nonlinear Control 7(3): 561-580. · Zbl 0875.93360 · doi:10.1002/(SICI)1099-1239(199706)7:6<561::AID-RNC291>3.0.CO;2-V
[40] Pardesi, M.S. (2005). Unmanned aerial vehicles-unmanned combat aerial vehicles: Likely missions and challenges for the policy-relevant future, Air and Space Power Journal19(3): 45-54.
[41] Pashikar, A.A., Sundararajan, N. and Saratchandran, P. (2007). Adaptive nonlinear neural controller for aircraft under actuator failures, Journal of Guidance, Control and Dynamics30(3): 835-847.
[42] Pedro, J.O. (1992). Numerical Simulations of TransportAircraft in Variable Wind Field, Ph.D. thesis, Faculty of Mechanical, Power and Aeronautical Engineering, Warsaw University of Technology, Warsaw, (in Polish, unpublished).
[43] Pedro, J.O. and Bigg, C.G. (2005). Development of a flexible embedded aircraft/Control system simulation facility, Proceedingsof the AIAA Modeling and Simulation Technologies,Conference and Exhibit, San Francisco, CA, USA, pp. 1-25.
[44] Pollini, L., Campa, G., Giulietti, F. and Innocenti, M. (2003). Virtual simulation set-up for UAVs aerial refuelling, Proceedingsof the AIAA Guidance, Navigation and ControlConference and Exhibit, Austin, TX, USA, Paper 2003-5682, pp. 1-8.
[45] Reiner, J., Balas, G.J. and Garrard, W.L. (1996). Flight control design using robust dynamic inversion and time scale separation, Automatica 32(11): 1493-1504. · Zbl 0871.93037 · doi:10.1016/S0005-1098(96)00101-X
[46] Soares, F., Burken, J. and Marwala, T. (2006). Neural network applications in advanced aircraft flight control system, a hybrid system, a flight test demonstration, in I. King, J.
[47] Wang, L-W. Chan and D. Wang Neural InformationProcessing, Lecture Notes in Computer Science, Vol. 4234, Springer-Verlag, Berlin/Heidelberg, pp. 684-691.
[48] Spaulding, C.M., Mansur, H.M., Tischler, M.B., Hess, R.A. and Franklin, J.A. (2005). Nonlinear inversion control for a ducted fan UAV, Proceedings of the AIAA AtmosphericFlight Mechanics Conference and Exhibit, San Francisco,CA, USA, pp. 1-26.
[49] Steinberg,M.L. (2001). Comparison of intelligent, adaptive, and nonlinear flight control laws, Journal of Guidance, Controland Dynamics 24(4): 693-699.
[50] Stengel, R.F. (2004). Flight Dynamics, Princeton University Press, Princeton, NJ.
[51] Steven, B.L. and Lewis, F.L. (1992). Aircraft Control and Simulation, John Wiley and Sons Inc., New York, NY.
[52] Thompson, K.E. (1998). F-16 uninhabited air combat vehicles, Technical report, Air Command and Staff College, Air University, Maxwell Air Force Base, AL.
[53] Vendra, S., Campa, G., Napolitano, M.R., Mammarella, M., Fravolini, M.L. and Perhinschi, M.G. (2007).
[54] Addressing corner detection issues for machine vision based UAV aerial refuelling, Machine Vision and Applications18(5): 261-273.
[55] Waishek, J., Dogan, A. and Blake, W. (2009). Derivation of the dynamics equations of receiver aircrft in aerial refueling, Journal of Guidance, Control and Dynamics32(2): 586-598.
[56] Wang, J., Patel, V.V., Cao, C. and Hovakimyan, N. (2008). Novel L1 adaptive control methodology for aerial refueling with guaranteed transient performance, Journal of Guidance,Control and Dynamics 31(1): 182-193.
[57] Wilson, J.R. (2005). UAV worldwide roundup 2005, AerospaceAmerica 43(9): 26-31.
[58] Withrow, M. (2004). UAV automated aerial refuelling: one step closer to reality, Air Vehicles Directorate News AFRL Magazine.
[59] Wong, K. and Bill, C. (1998). UAVs over Australia-market and capabilities, 13th Bristol International Conference onRPVs/UAVs, Bristol, UK.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.