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Wuhan University Journal of Natural Sciences

, Volume 24, Issue 5, pp 376–382 | Cite as

Development of Cueing Algorithm Based on “Closed-Loop” Control for Flight Simulator Motion System

  • Daoyang ZhuEmail author
  • Shaoli Duan
  • Da Fang
Computer Science
  • 1 Downloads

Abstract

The classical washout algorithm had fixed gains and manually constructed filters, so that it led to poor adaptability. Furthermore, it lost the sustained acceleration cues of high- and mid-frequency in cross-over (tilt-coordination) channel, and the acceleration of cross-over frequency was also limited by angular velocity limiter, so the false cues in flight simulation process were clearly perceived by pilots. The paper studied the characteristics of the classical washout algorithm and flight simulator motion platform, tried to redesign the source of cross-over acceleration channel and translation acceleration channel, and transferred the part of cross-over acceleration that was unsimulated sustained acceleration to translation acceleration channel. Comparisons were mainly made between classical washout algorithm and revised algorithm in a longitudinal/pitch direction. The evaluation was based on the implementation of human vestibular perception system. The results demonstrated that the revised algorithm could significantly reduce the phase lag, and improved the spikes tracking performance. Furthermore, sensory angular velocity and the error of sensory acceleration were strictly controlled within the threshold of human perception system, and the displacement was a little broader than the classical washout algorithm. Therefore, it was proved that the new algorithm could diminish the filters parameters and heighten the self-adaptability for the washout algorithm. In addition, the magnitude of false cues was remarkably reduced during flight simulator, and the workspace utilization of the motion platform was developed by “closed-loop” control system.

Key words

classical washout algorithm human vestibular system “closed-loop” control false cues 

CLC number

TP 391.9 V 211.73 

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References

  1. [1]
    Xing J F, Zeng X H, Huang H B. Four different six-degree-of-freedom architectures and comparison of their ability on workspace [J]. Journal of Naval University of Engineering, 2002, 14(1): 31–33(Ch).Google Scholar
  2. [2]
    Conrad B, Schmidt S F. Motion drive signals for piloted flight simulators [EB/OL]. [2019-03-08]. https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19700017803.pdf.
  3. [3]
    Conrad B, Schmidt S F. A study of techniques for calculating motion-drive signals for flight simulators [EB/OL]. [201903-08]. https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19710025909.pdf.
  4. [4]
    Bowles R L, Parrish R V, Dieudonne J E. Coordination adaptive washout for motion simulators [J]. Journal of Aircraft, 1975, 12(1): 44–50.CrossRefGoogle Scholar
  5. [5]
    Reid L D, Nahon M A. Flight simulation motion-base drive algorithms: Part 1—Developing and testing the equations [EB/OL]. [2019-04-12]. http://repository.tudelft.nl/assets/uuid:45b071c0-0568-4e8f-948f-dfa52d350665/296.pif
  6. [6]
    Reid L D, Nahon M A. Flight simulation motion-base drive algorithms: Part 2—Selecting the system parameters [EB/OL]. [2019-02-11]. http://repository.tudelft.nl/assets/uuid:4faf3129-88c9-4117-82e9-f9819601dafd/307.pdf.
  7. [7]
    Hwang T S, Yeh S K, Lin J R, et al. Adaptive motion washout filter design by using self-tuning fuzzy control [C]// Proceedings of the IEEE/ASME International Conference. Piscataway: IEEE, 2009: 811–815.Google Scholar
  8. [8]
    Wang X L, Li L, Zhang W H. Research on fuzzy adaptive washout algorithm of train driving simulator [J]. Journal of the China Railway Society, 2010, 32(2): 31–36(Ch).Google Scholar
  9. [9]
    Hsu C H, Liang S F, Lin C J, et al. An implementation of functional neural fuzzy controller for the electrical 6-DOF Stewart platform [C]// Proceedings of the System Science and Engineering (ICSSE). New York: IEEE, 2011: 292–297.Google Scholar
  10. [10]
    Asadi H, Mohamed S, Nahavandi S. Incorporating human perception with the motion washout filter using fuzzy logic control [J]. Mechatronics, IEEE/ASME Transactions on, 2015, 20(6): 3276–3284.CrossRefGoogle Scholar
  11. [11]
    Hoedemaeker M, Brookhuis K A. Behavioral adaptation to driving with an adaptive cruise control (ACC) [J]. Transportation Research Part of Traffic Psychology & Behavior, 1998, 1(2): 95–106.CrossRefGoogle Scholar
  12. [12]
    Dong Y L, Xu C X, Tang J L, et al. Design and test research of washout filter for 6-DOF platform [J]. Journal of Mechanical Engineering, 2010, 46(3): 53–58(Ch).CrossRefGoogle Scholar
  13. [13]
    Yang Y, Huang Q T, Han J W. Adaptive washout algorithm based on the parallel mechanism motion range [J]. Systems Engineering & Electronics, 2010, 32(12): 2716–2720.Google Scholar
  14. [14]
    Luo Z H, Wei Y D, Zhou X J, et al. Research on variable input washout algorithm for Stewart platform vehicle simulator [J]. Journal of Zhejiang University, 2013, 47(2): 238–243(Ch).Google Scholar
  15. [15]
    Wu W. Development of Cueing Algorithm for the Control of Simulator Motion Systems [D]. New York: State University of New York at Binghamton, 1997.Google Scholar
  16. [16]
    Wu W, Cardullo F M. Is there an optimum cueing algorithm [C]// AIAA Modeling and Simulation Technologies Conference. Los Angeles: AIAA, 1997: 23–29.Google Scholar
  17. [17]
    Houck J A, Telban R J, Cardullo F M. Developments in human centered cueing algorithms for control of flight simulator motion systems[C]// AIAA Modelling & Simulation Technologies Conference. New York: AIAA, 1999: 463–474.Google Scholar
  18. [18]
    Sivan R, Ish-Shalom J, Huang J K. An optimal control approach to the design of moving flight simulators [J]. IEEE Transactions on Systems Man & Cybernetics, 1982, 12(6): 818–827.CrossRefGoogle Scholar
  19. [19]
    Ariel D, Sivan R. False cue reduction in moving flight simulators [J]. IEEE Transactions on Systems, Man and Cybernetics, 1984, 14(4): 665–671.CrossRefGoogle Scholar
  20. [20]
    Telban R, Cardullo F, Houck J. A nonlinear, human-centered approach to motion cueing with a neurocomputing solver [C]// AIAA Modeling and Simulation Technologies Conference and Exhibit. New York: AIAA, 2002: 5–8.Google Scholar
  21. [21]
    Meiry J L. The vestibular system and human dynamic space orientation [EB/OL]. [2019-03-18]. https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19670001428.pdf.
  22. [22]
    Fernandez C, Goldberg J M. Physiology of peripheral neurons innervating semicircular canals of the squirrel monkey [J]. Journal of Neurophysiology, 1971, 34(4): 661–675.CrossRefGoogle Scholar
  23. [23]
    Young L R, Oman C M. Model for vestibular adaptation to horizontal rotation [J]. Aerospace Medicine, 1969, 40(10): 1076–1098.Google Scholar

Copyright information

© Wuhan University and Springer-Verlag GmbH Germany 2019

Authors and Affiliations

  1. 1.College of Intelligent ManufacturingWuhan Technical College of CommunicationsWuhan, HubeiChina

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