Hostname: page-component-586b7cd67f-gb8f7 Total loading time: 0 Render date: 2024-11-29T08:01:53.421Z Has data issue: false hasContentIssue false
  • English
  • Français

Validation of mathematical models for helicopter flight simulators past, present and future challenges

Published online by Cambridge University Press:  27 January 2016

M. D. Pavel ,
M. White ,
G. D. Padfield ,
G. Roth ,
M. Hamers  and
A. Taghizad
M. D. Pavel*
Affiliation:
Faculty of Aerospace Engineering, Delft University of Technology, Delft, The Netherlands
M. White
Affiliation:
School of Engineering, The University of Liverpool, Liverpool, UK
G. D. Padfield
Affiliation:
School of Engineering, The University of Liverpool, Liverpool, UK
G. Roth
Affiliation:
EUROCOPTER Germany, Donauwoerth, Germany
M. Hamers
Affiliation:
German Aerospace Center – DLR, Lilienthalplatz, Braunschweig, Germany
A. Taghizad
Affiliation:
Office National d’Etudes et de Recherches Aerospatiales – ONERA, Salon Cedex Air, France
*
[email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

At the heart of a flight simulator resides the mathematical representation of aircraft behaviour in response to control inputs, atmospheric disturbances and system inputs including failures and malfunctions. While this mathematical model can never be wholly accurate, its fidelity, in comparison with real world behaviour, underpins the usefulness of the flight simulator. The present paper examines the state of the art achieved in validating mathematical models for helicopter simulators, addressing the strengths and weaknesses of the present European standard for the qualification of helicopter flight simulators, JAR FSTD-H (previously JAR-STD-1H/2H/3H). Essential questions are examined, such as: What is the required model fidelity to guarantee a simulation is sufficiently representative to be fit for purpose? Are the tolerances set in the current standards fine enough that they lead to only minor changes in handling qualities? What is an acceptable tuning process for the simulation? What is the effect of modelling fidelity on the overall pilot control strategy? What is the relationship between the settings of the simulator cueing environment and the behaviour of the pilot? What is the industrial experience on qualification of flight simulators that might usefully inform developments? Many of these questions were addressed in Europe in a previous GARTEUR Action Group (AG) HC/AG-12 the results of which are documented in this paper. Solutions are proposed for improving the current JAR-FSTD standard with respect to validation of mathematical models.

Type
Research Article
Information
The Aeronautical Journal , Volume 117 , Issue 1190 , April 2013 , pp. 343 - 388
Copyright
Copyright © Royal Aeronautical Society 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Anon. JAR-FSTD H Helicopter Flight Simulation Training Devices, Joint Aviation Authorities, 2008.Google Scholar
2. Anon. JAR-STD 1H Helicopter Flight Simulators, Joint Aviation Authorities, 2001.Google Scholar
3. Anon. JAR-STD 2H Helicopter Flight Training Devices, Joint Aviation Authorities, 2003.Google Scholar
4. Anon. JAR-STD 3H Helicopter Flight & Navigation Procedural Trainers, Joint Aviation Authorities, 2002.Google Scholar
5. Anon. FAA AC 120-63 Helicopter Simulator Qualification. Federal Aviation Administration Advisory Circular, FAA AC, 1994.Google Scholar
6. Anon. NAWCSTD Specification Inputs For Military Simulator Flight Fidelity Validation Tests & Tolerances – Rotary Wing Aircraft, 2009.Google Scholar
7. Anon. Aeronautical Design Standard-33E-PRF, Performance Specification, Handling Qualities Requirements for Military Rotorcraft. US Army AMCOM, Redstone, Alabama, USA, 21 March 2000.Google Scholar
8. Scannapienco, L. et al, HELISIM: From Engineering Simulation to Level D Tarining Simulation, 60th Annual Forum of the American Helicopter Society, 7-10 June 2004, Baltimore, MD, USA.Google Scholar
9. Casolaro, D., Dequin, A.-M. and Gaulene, P. Eurocopter Experience in Flight Loop Development for Level D Training Simulator, 30th European Rotorcraft Forum, Marseilles, France, 14-16 September 2004.Google Scholar
10. Romanzi, E., Allain, C. and Gaulène, P.E. Flight Loop Development For Training Simulation By Industry Last Progress, 37th European Rotorcraft Forum, Gallarate, Italy, 13-15 September 2011.Google Scholar
11. Padfield, G.D. et al Final Report of Action Group HC/AG-12: Validation Criteria for Helicopter Realtime Simulation Models, April 2006.Google Scholar
12. Padfield, G.D. et al Validation Criteria for Helicopter Real-time Simulation Models; Sketches from the Work of GARTEUR HC/AG-12. 30th European Rotorcraft Forum, Marseilles, France, September 2004.Google Scholar
13. Padfield, G.D. et al Simulation fidelity of real-time helicopter simulation models, 61st Annual Forum of the American Helicopter Society, Grapevine, Texas, USA, June 2005.Google Scholar
14. Hess, R.A. and Malsbury, T. Closed Loop assessment of flight simulator fidelity, J Guidance, Control and Dynamics, 1991, 14, (1), pp 191–197.Google Scholar
15. Hess, R.A. and Siwakosit, W. Assessment of flight simulator fidelity in multi-axis tasks including visual cue quality, J Aircraft, 2001, 38, (4), pp 607–614.Google Scholar
16. Schroeder, J.A., Chung, W.W.Y. and Hess, R.A. Evaluation of motion fidelity criterion with visual scene changes, J Aircraft, 2000, 37, (4), pp 580–587.Google Scholar
17. Padfield, G.D., Charlton, M.T. and McCallum, A.T. The Fidelity of Hi-Fi Lynx on The DERA Advanced Flight Simulator Using ADS-33 Handling Qualities Metrics, DRA/AS/FDS/TR96103/1, December 1996, pp 1–152.Google Scholar
18. McCallum, A.T. and Charlton, M.T. Structured Approach to Helicopter Simulator Acceptance, The Challenge of Realistic Rotorcraft Simulation, Royal Aeronautical Society, London, UK, November 2001.Google Scholar
19. Advani, S.K. and Wilkinson, C.H. Dynamic Interface Modelling and Simulation – A Unique Challenge, Royal Aeronautical Society Conference on Helicopter Flight Simulation. London, UK, 2001.Google Scholar
20. Roscoe, M.F. and Thompson, J.H. JSHIP’s Dynamic Interface Modelling and Simulation Systems: A Simulation of the UH-60A Helicopter/LHA Shipboard Environment Task, 59th Annual Forum of the American Helicopter Society, Phoenix, AZ, USA, May 2003.Google Scholar
21. Haverdings, H. et al, Final report of GARTEUR Helicopter Action Group HC(AG-09) on: Mathematical modelling for prediction of helicopter flying qualities Phase 3, GARTEUR TP-116, November 1999.Google Scholar
22. Haverdings, H. et al, Mathematical modelling for the prediction of flying qualities within GARTEUR – phase 3, 26th European Rotorcraft Forum, Den Hague, The Netherlands, 26-29 September 2000.Google Scholar
23. Mitchell, D.G., Hoh, R.H., He, C. and Strope, K. Development of an Aeronautical Design Standard for Validation of Military Helicopter Simulators. 62nd Annual Forum of the American Helicopter Society, Phoenix, AZ, May 2006.Google Scholar
24. Tischler, M. System Identification Methods for Aircraft Flight Control Development and Validation. NASA TM-110369, October 1995.Google Scholar
25. White, M., Perfect, P., Padfield, G.D., Gubbels, A.W. and Berryman, A. Progress in the Development of Unified Fidelity Metrics for Rotorcraft Flight Simulators. 66th Annual Forum of the American Helicopter Society, 11-13 May 2010, Phoenix, AZ, USA.Google Scholar
26. Perfect, P., White, M., Padfield, G.D., Gubbels, A.W. and Berryman, A. Integrating Predicted and Perceived Fidelity for Flight Simulators. 36th European Rotorcraft Forum. 7-9 September 2010, Paris, France.Google Scholar
27. Cooper, G.E. and Harper, R.P. Jr. The Use of Pilot Rating in the Evaluation of Aircraft Handling Qualities, NASA Technical Note, TN-D-5153, April 1969.Google Scholar
28. Zivan, L. and Tischler, M.B. Development of a full flight envelope helicopter simulation using system identification, J American Helicopter Society, April 2010, 55, (2), pp 3–15.Google Scholar
29. Lu, L., Padfield, G.D. and Jump, M. Investigation of rotorcraft-pilot couplings under flight-path constraint below the minimum-power speed, Aeronaut J, 2010, 11 4, (1155), pp 25–34.Google Scholar
30. Lu, L., Padfield, G.D. and Jump, M. Optical Tau in Boundary-Avoidance Tracking – A New Perspective on Pilot-Induced Oscillations, 36th European Rotorcraft Forum, Salons de l’Aveyron Conference Centre, Paris, France, 2010.Google Scholar
31. McRuer, D.T. and Krendel, E.S. Mathematical models of human pilot behaviour. AGARD-AG-188, 1974.Google Scholar
32. Federal Aviation Administration, Advanced Simulation Plan, 14 C.F.R. Part 121, Appendix H, 1980.Google Scholar
33. Irving, D. Regulatory Standards: More of the same, or Time to start thinking about new Approaches?, SimTecT 2005 Keynote Address, SimTecT 2005 Simulation Conference and Exhibition, 9–12 May 2005, Sydney, Australia, http://www.siaa.asn.au/simtect/2005/.Google Scholar
34. Baarspul, M.A. Review of flight simulation techniques, Progress in Aerospace Sciences, 1990, 27, (1), pp 1–120.Google Scholar
35. Anon. JAR-STD 1A Aeroplane Flight Simulators. Joint Aviation Requirements Standard, 2001.Google Scholar
36. Anon. FAA AC 120-40B Airplane Simulator Qualifications. Federal Aviation Administration Advisory Circular, July 1991.Google Scholar
37. Anon. JAR-FSTD A Aeroplane Flight Simulation Training Devices, 2008.Google Scholar
38. Anon. FAA AC Guidance and Procedures for Helicopter Simulator and Visual System Evaluations. Federal Aviation Administration Advisory Circular, 1992.Google Scholar
39. Anon. FAR Sec. 135.335 Approval of aircraft simulators and other training devices. Code of Federal Regulations, Title 14, 2, revised 1 January 2003.Google Scholar
40. Anon. FAA AC 120-40B Airplane Simulator Qualification. Federal Aviation Administration Advisory Circular 1991.Google Scholar
41. Anon. Manual of Criteria for the Qualification of Flight Simulation Training Devices, Volume I – Aeroplanes, Third Edition, International Civil Aviation Organization Doc 9625 AN/938 2009.Google Scholar
42. Tharp, P. The Contribution of Flight Simulation to Aviation, Royal Aeronautical Society Flight Simulation Group Conference, 9-10 November 2011, London, UK.Google Scholar
43. Van der Meer, B., Yilmaz, D., Stoop, J.A.A.M. and Pavel, M.D. Helicopter Safety: A Contradiction In Terms? – An Overview Of The Status At The Beginning Of The 21st Century, 37th European Rotorcraft Forum, Gallarate (Varese) Italy, 13-15 September, 2011.Google Scholar
44. Joint Helicopter Safety Implementation Team (JHSIT) Helicopter Training Toolkit, IHST 2009.Google Scholar
45. Benoit, B. et al HOST, a General Helicopter Simulation Tool for Germany and France, 56th American Helicopter Society Annual Forum, Virginia Beach, Virginia, USA, May 2000.Google Scholar
46. Strachan, I. Helicopter Flight Simulation Today – An Overview, Military Simulation & Training Magazine, Issue 2/2008, http://halldale.com/insidesnt/helicopter-flight-simulation-today-overview.Google Scholar
47. Mcruer, D.T. et al Aviation Safety And Pilot Control. Understanding and Preventing Unfavorable Pilot-Vehicle Interactions, ASEB National Research Council, National Academy Press, Washington DC, USA 1997.Google Scholar
48. Hampson, B. The use of full flight simulators & synthetic training devices in the fields of helicopter training, testing & checking, AIAA Modeling and Simulation Technologies Conference and Exhibit 14-17 August 2000 Denver, CO, USA, AIAA-2000-3974.Google Scholar
49. Hamers, M. and Von GRünhagen, W. Nonlinear Helicopter Model Validation Applied to Realtime Simulations. 53rd American Helicopter Society Annual Forum, Virginia Beach, Virginia, USA, 29 April – 1 May 1997.Google Scholar
50. Rohm, B.N. FAA/JAA Harmonization of FAR 33/JAR-E Engine Certification Regulations. 53rd American Helicopter Society Annual Forum, Virginia Beach, Virginia, USA, 29 April – 1 May 1997.Google Scholar
51. Du Val, R. and He, W. Chengjian. Integration of Simulation Validation Tools with a Comprehensive Rotorcraft Analysis for Physically Based Validation with a Comprehensive Rotorcraft Analysis. American Helicopter Society Vertical Lift Aircraft Design Conference, San Francisco, CA, USA, January 2000.Google Scholar
52. He, C., Goericke, J. and Kang, H. Modeling Enhancements for Physics-Based Simulation Validations, 61st Annual Forum of the American Helicopter Society, Grapevine, TX, USA, 1-3 June 2005.Google Scholar
53. Kothmann, B.D., Keller, J.D. and Curtiss, H.C. Jr., On Aerodynamic Modelling for Rotorcraft Flight Dynamics. 22nd European Rotorcraft Forum, Brighton, UK, September 1996.Google Scholar
54. Smith, S.J. Helicopter Simulation Modeling Techniques for Meeting FAA AC 120-63 Level D Qualification Requirements, 56th Annual Forum of the American Helicopter Society, Virginia Beach, Virginia, USA, 2-4 May 2000.Google Scholar
55. Anon. FAA AC-29A Certification of Transport Category Rotorcraft. Federal Aviation Administration Advisory Circular, 1987.Google Scholar
56. Dearing, M.G., Schrouder, J.A., Sweet, B.T. and Kaiser, M.K. Effects of Visual texture, Grids, and Platform Motion on Unpowered Helicopter Landings, AIAA Modeling and Simulation Technologies Conference and Exhibit, Montreal, Quebec, Canada, 6-9 August 2001, AIAA 2001-37387.Google Scholar
57. Decker, W.A., Adam, C.F. and Gerdes, R.M. Pilot Use of Simulator Cues for Autorotation landings. 42nd Annual Forum of the American Helicopter Society, Washington DC, USA, June 1986.Google Scholar
58. Padfield, G.D. and White, M.D. Measuring simulation fidelity through an adaptive pilot model, Aerospace Science and Technology, July 2005, 9, (5), pp 400–408.Google Scholar
59. White, M.D., Padfield, G.D. and Armstrong, R. Progress in measuring simulation fidelity using an adaptive pilot model. 30th Annual Forum of the American Helicopter Society, Baltimore, Maryland, MD, USA, June 2004.Google Scholar
60. Padfield, G.D. The Tau of flight control, Aeronaut J, 2011, 11 5, (1171), pp 521–556.Google Scholar
61. Padfield, G.D. and White, M.D. Flight Simulation in Academia; HELIFLIGHT in its first year of operation, Aeronaut J, September 2003, 107, (1075), pp 529–538.Google Scholar
62. White, M.D., Perfect, P., Padfield, G.D., Gubbels, A.W. and Berryman, A.C., Acceptance testing of a rotorcraft flight simulator for research and teaching: the importance of unified metrics. Proceedings of the 35th European Rotorcraft Forum, Hamburg, Germany, September 2009.Google Scholar
63. Padfield, G.D., Lee, D. and Bradley, R. How do pilots know when to stop, turn or pull-up? Developing guidelines for the design of vision aids, J American Helicopter Society, April 2003, 48, (2), pp 108–119.Google Scholar
64. Padfield, G.D., Jones, J.P., Charlton, M.T., Howell, S. and Bradley, R. Where Does the Workload Go When Pilots Attack Manoeuvres? – An Analysis of Results from Flying Qualities Theory and Experiment, 20th European Rotorcraft Forum, Amsterdam, The Netherlands, October 1994.Google Scholar
65. Perfect, P., Timson, E., White, M.D., Padfield, G.D., Erdos, R. and Gubbels, A.W. A Rating Scale for Subjective Assessment of Simulator Fidelity, Paper 173 presented at the 37th European Rotorcraft Forum, Gallarate, September 2011.Google Scholar
66. Timson, E., Perfect, P., White, M.D, Padfield, G.D., Erdos, R. and Gubbels, A.W. Pilot Sensitivity to Flight Model Dynamics in Flight Rotorcraft Simulation, Paper 172, presented at the 37th European Rotorcraft Forum, Gallarate, 13-15 September 2011.Google Scholar
67. Roza, Z.C. Simulation Fidelity Theory and Practice, A Unified Approach to Defining, Specifying and Measuring the Realism of Simulations, PhD thesis, Delft University of Technology, DUP Science, 2004.Google Scholar
68. Steurs, M., Mulder, M. and van Paassen, M.M. A Cybernetic Approach to Assess Flight Simulator Fidelity, Proceedings of the AIAA Modelling and Simulation Technologies Conference and Exhibit, Providence (RI), No. AIAA-2004-5442, 16-19 August 2004.Google Scholar
69. Nieuwenhuizen, F.M., Zaal, P.M.T., Mulder, M. and van Paassen, M.M. A New Multi-Channel Pilot Model Identification Method for Use in Assessment of Simulator Fidelity, Proceedings of the AIAA Modeling and Simulation Technologies Conference and Exhibit, Keystone (CO), No. AIAA-2006-6629, 21–24 August 2006.Google Scholar
70. Herman, J. Damveld, A Cybernetic Approach to Assess the Longitudinal Handling Qualities of Aeroelastic Aircraft, Delft University of Technology, Faculty of Aerospace Engineering, 2009.Google Scholar
71. Pool, D.M., Mulder, M., van Paassen, M.M. and van der Vaart, J.C. Effects of peripheral visual and physical motion cues in roll-axis tracking tasks, J Guidance, Control and Dynamics, 2008, 31, (6), pp 1608–1622.Google Scholar
72. Mulder, M. and Mulder, J.A. Cybernetic Analysis of perspective flight-path display dimensions, J. Guidance, Control and Dynamics, 2005, 28, (3), pp 398–411.Google Scholar
73. Mulder, M. Cybernetics of Tunnel-in-the-Sky Displays, PhD thesis, Delft University of Technology, Faculty of Aerospace Engineering, 1999.Google Scholar
74. Wiener, N. Cybernetics or Control and Communication in the Animal and the Machine, Cambridge, MIT Press, 1948.Google Scholar
75. Mulder, M., van Paassen, M.M. and Boer, E.R. Exploring the roles of information in the control of vehicular locomotion, kinematics and dynamics to cybernetics. PRESENCE: Tele-operators and Virtual Environments, 2004, 13, (5), pp 535–548.Google Scholar
76. Schouten, A.C. Proprioceptive Reflexes and Neurological Disorders. PhD dissertation, Faculty of Mechanical Engineering, Delft University of Technology, 2004.Google Scholar
77. De Vlugt, E. Identification of Spinal Reflexes, PhD dissertation, Faculty of Mechanical Engineering, Delft University of Technology, 2004.Google Scholar
78. Van den Hof, P.M.J. and Schrama, R.J.P. Identification and control closed-loop issues, Automatica, 1995, 31, (12), pp 1751–1770.Google Scholar
79. Van den Hof, P.M.J. Closed-loop Issues in system identification, Annual Reviews in Control, 1998, 22, pp 173–186.Google Scholar
80. Grant, P.R. and Schroeder, J.A. Modelling Pilot Control Behaviour for Flight Simulator Design and Assessment, in: Proceedings of the AIAA Guidance, Navigation, and Control Conference, Toronto, Canada, 2-5 August 2010, Washington, DC, USA, American Institute for Aeronautics and Astronautics.Google Scholar
81. Schroeder, J.A. and Grant, P.R. Pilot Behavioral Observations in Motion Flight Simulation, in: Proceedings of the AIAA Guidance, Navigation, and Control Conference, Toronto, Canada, 2-5 August, Washington, DC, USA, American Institute for Aeronautics and Astronautics, 2010.Google Scholar