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All issues Volume 26 / No 6 (December 2021) Wuhan Univ. J. Nat. Sci., 26 6 (2021) 513-520 References
Open Access
Issue
Wuhan Univ. J. Nat. Sci.
Volume 26, Number 6, December 2021
Page(s) 513 - 520
DOI https://doi.org/10.1051/wujns/2021266513
Published online 17 December 2021
  1. Conrad B, Schmidt S F. Motion Drive Signals for Piloted Flight Simulators [EB/OL]. [2021-08-15]. https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19700017803.pdf. [Google Scholar]
  2. Nehaoua L, Amouri A, Arioui H. Classic and adaptive washout comparison for a low cost driving simulator [C]// Proceedings of the 20th IEEE International Symposium on Intelligent Control and the 13th Mediterranean Conference on Control and Automation. Piscataway: IEEE, 2005: 586-591. [Google Scholar]
  3. Asadi H, Mohammadi A, Mohamed S, et al. A particle swarm optimization-based washout filter for improving simulator motion fidelity [C]// Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). New York: IEEE, 2016: 1963-1968. [Google Scholar]
  4. Bowles R L, Parrish R V, Dieudonne J E. Coordinated adaptive washout for motion simulators [J]. Journal of Aircraft, 1975, 12(1): 44-50. [Google Scholar]
  5. 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 and Cybernetics, 1982, 12(6): 818-827. [Google Scholar]
  6. Reid L D, Nahon M A. Flight Simulation Motion-base Drive Algorithms: Part 1—Developing and Testing the Equations[EB/OL]. [2021-08-15]. http://repository.tudelft.nl/assets/uuid:45b071c0-0568-4e8f-948f-dfa52d350665/296.pdf. [Google Scholar]
  7. Telban R, Wu W, Cardullo F M. Motion cuing algorithm development: Initial investigation and redesign of the algorithms [EB/OL]. [2021-08-15]. https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20000041705.pdf. [Google Scholar]
  8. Asadi H, Chee P L. A genetic algorithm-based nonlinear scaling method for optimal MCA in driving simulator [J]. Proc IMechE Part I: Journal of Systems and Control Engineering, 2018, 232(8): 1025-1038. [CrossRef] [Google Scholar]
  9. Luo Z H, Wei Y D, Zhou X J. Research on variable input MCA for Stewart platform vehicle simulator [J]. Journal of Zhejiang University (Engineering Science), 2013, 47(2): 238-243(Ch). [Google Scholar]
  10. Chen W, Jiang G H, Chao J G. Signal scaling strategies for motion-base spaceflight simulators [J]. Journal of Beijing University of Aeronautics and Astronautics, 2012, 38(3): 324-329. [Google Scholar]
  11. Wu W. Development of Cueing Algorithm for the Control of Simulator Motion Systems [D]. New York: Binghamton University, 1997. [Google Scholar]
  12. Wu W, Cardullo F. Is there an optimum motion cueing algorithm? [C]//AIAA Modeling and Simulation Technologies Conference. Reston: AIAA, 1997: 3506. [Google Scholar]
  13. Zaychik K B, Cardullo F M. Nonlinear Motion Cueing Algorithm: Filtering at Pilot Station and Development of the Nonlinear Optimal Filters for Pitch and Roll [EB/OL]. [2021- 08-06]. https://ntrs.nasa.gov/citations/20120008933.pdf. [Google Scholar]
  14. Telban R J, Cardullo F M, Houck J A. A nonlinear, human-centered approach to motion cueing with a neurocomputing solver [C]// AIAA Modeling and Simulation Technologies Conference and Exhibit. Reston: AIAA, 2002: 4692. [Google Scholar]
  15. Pahlevaninezhad M, Das P, Drobnik J, et al. A nonlinear optimal control approach based on the control-Lyapunov function for an AC/DC converter used in electric aircrafts [J]. IEEE Transactions on Industrial Informatics, 2012, 8(3): 596-614. [Google Scholar]
  16. Asadi H, Mohamed S, Nahavandi S. Incorporating human perception with the motion washout filter using fuzzy logic control [J]. IEEE/ASME Transactions on Mechatronics, 2015, 20(6): 3276-3284. [Google Scholar]
  17. Mohammadi A, Asadi H, Mohamed S, et al. Optimizing model predictive control horizons using genetic algorithm for motion cueing algorithm [J]. Expert Systems with Applications, 2018, 92: 73-81. [CrossRef] [Google Scholar]
  18. Telban R J, Cardullo F M. MCA development: Human centered linear and nonlinear approaches [EB/OL]. [2021-09-06]. https://ntrs.nasa.gov/citations/20050180246.pdf. [Google Scholar]
  19. Hosman R, van der Vaart J C.Vestibular Models and Thresholds of Motion Perception: Results of Tests in a Flight Simulator [R]. Delft: Delft University of Technology, 1978. [Google Scholar]
  20. Zhu D Y, Duan S L, Shang J Q, et al. A novel nonlinear scaling method for optimal motion cueing algorithm in flight simulator [J]. Wuhan University Journal of Natural Sciences, 2020, 25(5): 452-460. [Google Scholar]
  21. Nahon M A, Reid L D. Simulator motion-drive algorithms—A designer’s perspective [J]. J Guid ContrDynam, 1990, 13(2): 356-362. [NASA ADS] [CrossRef] [Google Scholar]

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