Learning UAV stability and control derivatives using gaussian processes

IEEE Transactions on Robotics

Volumn 29, Issue 4, 2013, Pages 813-824

  Hemakumara, Prasad ^a   Sukkarieh, Salah ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

Author keywords

Gaussian processes; system identification; unmanned aerial vehicles (UAVs)

Indexed keywords

EXPERIMENTAL DATUM; GAUSSIAN PROCESSES; NONLINEAR FLIGHT DYNAMICS; PARAMETERIC MODELS; STABILITY AND CONTROL; SYSTEM IDENTIFICATION METHODS; UNCERTAINTY ESTIMATES; UNMANNED AERIAL VEHICLE (UAVS);

DYNAMIC RESPONSE; FLIGHT CONTROL SYSTEMS; FLIGHT ENVELOPES; FLIGHT SIMULATORS; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); IDENTIFICATION (CONTROL SYSTEMS); SYSTEM STABILITY;

UNMANNED AERIAL VEHICLES (UAV);

EID: 84881531835     PISSN: 15523098     EISSN: None     Source Type: Journal    
DOI: 10.1109/TRO.2013.2258732     Document Type: Article

References (39)

1. V. Klein and E. A. Morelli, Aircraft System Identification: Theory and Practice (Education Series). Reston, VA, USA: Amer. Inst. Aeronaut. Astronaut., 2006.
2. H. A. Rediess "An overview of parameter estimation techniques and applications in aircraft flight testing." Parameter Estimation Techniques and Applications in Aircraft Flight Testing, Nat. Aeronaut. Space Admin., Washington, DC, USA, NASA, Tech. Note D-7647, Apr. 1974.
3. R. V. Jategaonkar, Flight Vehicle System Identification - A Time Domain Methodology. vol. 216, Reston, VA, USA: Amer. Inst. Aeronaut. Astronaut., 2006.
4. R. K. Mehra, D. E. Stepner, and J. S. Tyler, "Maximum likelihood identification of aircraft stability and control derivatives," J. Aircraft, vol. 11, pp. 81-89, 1974.
5. V.Klein, "Estimation of aircraft aerodynamic parameters from flight data," Progr. Aerosp. Sci., vol. 26, no. 1, pp. 1-77, 1989. (Pubitemid 20690584)
6. R. E.Maine and K.W. Iliff, "Application of parameter estimation to aircraft stability and control: The output-error approach," Ames Res. Center, Nat. Aeronautics Space Admn., Moffett Field, CA, USA, NASA Ref. Publ. 1168, 1986.
7. V. Klein, "Aircraft parameter estimation in frequency domain," presented at the AIAA Atmospheric Flight Mech. Conf., Palo Alto, CA, USA, 1998.
8. E. A.Morelli, "Real-time parameter estimation in the frequency domain," J. Guid. Control Dyn., vol. 23, no. 5, pp. 812-818, 2000.
9. H. Wu, D. Sun, and Z. Zhou, "Model identification of a micro air vehicle in loitering flight based on attitude performance evaluation," IEEE Trans. Robot., vol. 20, no. 4, pp. 702-712, Aug. 2004.
10. A. Coates, P. Abbeel, and A. Y. Ng, "Learning for control from multiple demonstrations," in Proc. 25th Int. Conf. Mach. Learn., 2008, pp. 144- 151.
11. P. Abbeel, A. Coates, M. Quigley, and A. Y. Ng, "An application of reinforcement learning to aerobatic helicopter flight," in Proc. 19th Conf. Adv. Neural Inf. Process. Syst., 2006, pp. 1-8.
12. D. J. Linse and R. F. Stengel, "Identification of aerodynamic coefficients using computational neural networks," J. Guid. Control Dyn., vol. 16, no. 6, pp. 1018-1025, 1993.
13. M. J. Allen and R. P. Dibley, "Modeling aircraft wing loads from flight data using neural networks," Dryden Flight Res. Center, Nat. Aeronautics Space Admn., Edwards, CA, USA, NASA Tech. Paper H-2546, 2003.
14. J. J. Burken, C. E. Hanson, J. A. Lee, and J. T. Kaneshige, "Flight test comparison of different adaptive augmentations of fault tolerant control laws for a modified F-15 aircraft," presented at the AIAA Unmanned Unlimited Conf., Seattle, WA, USA, Apr. 2009.
15. J. Ko, D. J. Klein, D. Fox, and D. Haehnel, "Gaussian processes and reinforcement learning for identification and control of an autonomous blimp," in Proc. IEEE Int. Conf. Robot. Autom., 2007, pp. 742-747. (Pubitemid 350140274)
16. D. Grimes, R. Chalodhorn, and R. Rao, "Dynamic imitation in a humanoid robot through nonparametric probabilistic inference," in Proc. Robot.: Sci. Syst., 2006, pp. 199-206.
17. P. Goovaerts, Geostatistics for Natural Resources Evaluation. Oxford, U.K.: Oxford Univ. Press, 1997.
18. P. Boyle and M. Frean, "Dependent Gaussian processes," in Proc. 17th Conf. Adv. Neural Inf. Process. Syst., 2005, pp. 217-224.
19. P. Boyle, "Gaussian processes for regression and optimisation," Ph.D. dissertation, Victoria Univ. Wellington, Wellington, New Zealand, 2006.
20. P. Hemakumara and S. Sukkarieh, "Non-parametric UAV system identification with dependent Gaussian processes," in Proc. IEEE Int. Conf. Robot. Autom., 2011, pp. 4435-4441.
21. M. B. Tischler and R. K. Remple, Aircraft and Rotorcraft System Identification: Engineering Methods with Flight Test Example, (Education Series). Reston, VA, USA: Amer. Inst. Aeronaut. Astronaut., 2006.
22. C. E. Rasmussen and C. K. I. Williams, Gaussian Processes for Machine Learning. Cambridge, MA, USA: MIT Press, 2006.
23. S. Vasudevan, F. Ramos, E. Nettleton, and H. Durrant-Whyte, "Nonstationary dependent Gaussian processes for data fusion in large-scale terrain modeling," in Proc. IEEE Int. Conf. Robot. Autom., 2011, pp. 1875- 1882.
24. Nat. Aeronautics Space Admn., (1998). Ames-Dryden-1 oblique wing aircraft. [Online]. Available: http://www.dfrc.nasa.gov/Gallery/Graphics/AD-1/ index.html
25. A. G. Sim and R. E. Curry, "Flight characteristics of the AD-1 obliquewing research aircraft," Ames Research Center, Nat. Aeronautics Space Admn., Moffett Field, CA, USA, NASA Tech. Paper 2223, 1985.
26. R. Curry andA. Sim, "In-flight total forces,moments, and static aeroelastic characteristics of an oblique-wing research airplane," Ames Res. Center, Nat. Aeronautics Space Admn., Moffett Field, CA, USA, NASA Tech. Paper 2284, 1984.
27. A. G. Sim and R. E. Curry, "Flight-determined aerodynamic derivatives of the AD-1 oblique-wing research airplane," Ames Res. Center, Nat. Aeronautics Space Admn., Moffett Field, CA, USA, NASA Tech. Paper 2222, 1984.
28. R. E. Maine and K. W. Iliff, "The theory and practice of estimating the accuracy of dynamic flight-determined coefficients," Dryden Flight Res. Center, Nat. Aeronautics Space Admn., Edwards, CA, USA, NASA Ref. Publ. 1077, 1981.
29. R.Koehler andK.Wilhelm, "Auslegung von eingangssignalen fur die kennwertermittlung ('design of input signals for identification')" (inGerman), DFVLR Inst. fur Flugmechanik, Brunswick, German, Rep. IB 154-77/40, 1977.
30. P. J. van Laarhoven and E. H. Aarts, Simulated Annealing: Theory and Applications. vol. 37, New York: Springer-Verlag, 1987.
31. E. Nettleton, "Decentralised architectures for tracking and navigation with multiple flight vehicles," Ph.D. dissertation, Univ. Sydney, Sydney, N.S.W., Australia, 2003.
32. D. Cole, A. Goktogan, and S. Sukkarieh, "The demonstration of a cooperative control architecture for UAV teams," in Experimental Robotics. New York, NY, USA: Springer-Verlag, 2008, pp. 501-510. (Pubitemid 351223291)
33. J. H. Kim, S. Sukkarieh, and S. Wishart, "Real-time navigation, guidance, and control of a UAV using low-cost sensors," in Field and Service Robotics. New York, NY, USA: Springer-Verlag, 2006, pp. 299-309. (Pubitemid 44430508)
34. A. Krause, A. Singh, and C. Guestrin, "Near-optimal sensor placements in Gaussian processes: Theory, efficient algorithms and empirical studies," J. Mach. Learn. Res., vol. 9, pp. 235-284, 2008. (Pubitemid 351469021)
35. J. H. Kim and S. Sukkarieh, "Airborne simultaneous localisation and map building," in Proc. IEEE Int. Conf. Robot. Autom., 2003, pp. 406-411.
36. M. Bryson and S. Sukkarieh, "Building a robust implementation of bearing-only inertial SLAM for a UAV," J. Field Robot., vol. 24, nos. 1-2, pp. 113-143, 2007. (Pubitemid 46464284)
37. G. Liu and A. A. Goldenberg, "Uncertainty decomposition-based robust control of robot manipulators," IEEE Trans. Control Syst. Technol., vol. 4, no. 4, pp. 384-393, Jul. 1996. (Pubitemid 126777701)
38. S. C. Liu, D. L. Tan, and G. J. Liu, "Robust leader-follower formation control of mobile robots based on a second order kinematics model," Acta Automatica Sinica, vol. 33, no. 9, pp. 947-955, 2007.
39. Y. Shen, A. Ng, and M. Seeger, "Fast Gaussian process regression using KD-trees," Adv. Neural Inf. Process. Syst., vol. 18, 2006.