Skip to main content

Flight Dynamics Modeling

  • Chapter
Unmanned Rotorcraft Systems

Part of the book series: Advances in Industrial Control ((AIC))

Abstract

In Chap. 6, we present a comprehensive modeling process to obtain a highly accurate nonlinear dynamical model for our unmanned systems, SheLion (also applicable to HeLion). We first derive a minimum-complexity model structure, which covers all the important dynamic features necessary for flight control law design. Based on this structured model, we develop a five-step procedure, a systematic combination of the first-principles and system identification approaches, to determine all the associated model parameters. We then carry out a thorough validation process to verify the fidelity of the flight dynamics model in the wide flight envelope. Finally, we proceed to determine the flight envelope of the obtained flight dynamics model, which is essential before proceeding to conduct flight control law design and flight experiments.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. ADS-33D-PRF. Aeronautical design standard performance specification handling qualities requirements for military rotorcraft. U.S. Army Aviation and Troop Command; 1996.

    Google Scholar 

  2. Cheng RP, Tischler MB, Schulein GJ. Rmax helicopter state-space model identification for hover and forward-flight. J Am Helicopter Soc. 2006;51:202–10.

    Article  Google Scholar 

  3. Civita ML, Messner W, Kanade T. Modeling of small-scale helicopters with integrated first-principles and integrated system identification techniques. Presented at 58th forum of American helicopter society, Montreal, Canada; 2002.

    Google Scholar 

  4. Curtiss HC Jr. Stability and control modeling. Vertica. 1988;12:381–94.

    Google Scholar 

  5. Gavrilets V, Mettler B, Feron E. Nonlinear model for a small-size acrobatic helicopter. Presented at AIAA guidance, navigation, and contr conf, Montreal, Canada; 2001.

    Google Scholar 

  6. Harris CM. Shock and vibration handbook. 4th ed. New York: McGraw-Hill; 1996.

    Google Scholar 

  7. Heffley RK, Bourne SM, Curtiss HC Jr, et al. Study of helicopter roll control effectiveness criteria [report]. NASA CR 177404; 1986.

    Google Scholar 

  8. Heffley RK, Mnich MA. Minimum-complexity helicopter simulation math model [report]. Technical Report. NASA Contractor Report 177476, NASA; 1988.

    Google Scholar 

  9. Jacobs EN, Sherman A. Airfoil section characteristics as affected by variations of the Reynolds number [report]. NACA Report 586; 1937.

    Google Scholar 

  10. Johnson W. Helicopter theory. Mineola: Dover Publications; 1994.

    Google Scholar 

  11. Kim SK, Tilbury DM. Mathematical modeling and experimental identification of an unmanned helicopter robot with flybar dynamics. J Robot Syst. 2004;21:95–116.

    Article  Google Scholar 

  12. Mettler BM. Identification, modeling and characteristics of miniature rotorcraft. Boston: Kluwer Academic Publishers; 2002.

    Google Scholar 

  13. Mettler BM, Tischler MB, Kanade T. System identification modeling of a small-scale unmanned rotorcraft for control design. J Am Helicopter Soc. 2002;47:50–63.

    Article  Google Scholar 

  14. Padfield GD. Helicopter flight dynamics: the theory and application of flying qualities and simulation modeling. Reston: AIAA Press; 1996.

    Google Scholar 

  15. Pelletier A, Mueller TJ. Low Reynolds number aerodynamics of low-aspect-ratio, thin/flat/ cambered-plate wings. J Aircr. 2000;37:825–32.

    Article  Google Scholar 

  16. Sathaye SS. Lift distributions on low aspect ratio wings at low Reynolds numbers [thesis]. Worcester Polytechnic Institute, Worcester, MA; 2004.

    Google Scholar 

  17. Shim DH, Kim HJ, Sastry S. Control system design for rotorcraft-based unmanned aerial vehicle using time-domain system identification. In: Proc IEEE conf contr appl, Anchorage, AK; 2000. p. 808–13.

    Google Scholar 

  18. Tischler MB, Remple RK. Aircraft and rotorcraft system identification: engineering methods with flight test examples. Reston: AIAA Press; 2006.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ben M. Chen .

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag London Limited

About this chapter

Cite this chapter

Cai, G., Chen, B.M., Lee, T.H. (2011). Flight Dynamics Modeling. In: Unmanned Rotorcraft Systems. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-0-85729-635-1_6

Download citation

  • DOI: https://doi.org/10.1007/978-0-85729-635-1_6

  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-634-4

  • Online ISBN: 978-0-85729-635-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics