http://iet.metastore.ingenta.com
1887

Dynamic inversion with zero-dynamics stabilisation for quadrotor control

Dynamic inversion with zero-dynamics stabilisation for quadrotor control

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Control Theory & Applications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

For a quadrotor, one can identify the two well-known inherent rotorcraft characteristics: underactuation and strong coupling in pitch-yaw-roll. To confront these problems and design a station-keeping and tracking controller, dynamic inversion is used. Typical applications of dynamic inversion require the selection of the output control variables to render the internal dynamics stable. This means that in many cases, perfect tracking cannot be guaranteed for the actual desired outputs. Instead, the internal dynamics of the feedback linearised system is stabilised using a robust control term. Unlike standard dynamic inversion, the linear controller gains are chosen uniquely to satisfy the tracking performance. Stability and tracking performance are guaranteed using a Lyapunov-type proof. Simulation with a typical nonlinear quadrotor dynamic model is performed to show the effectiveness of the designed control law in the presence of input disturbances.

References

    1. 1)
      • Koo, T.J., Sastry, S.: `Output tracking control design of a helicopter model based on approximate linearization', Proc. 37th Conf. Decision and Control, 1998, Tampa, FL, IEEE
    2. 2)
      • Gavrilets, V., Mettler, B., Feron, E.: `Dynamic model for a miniature aerobatic helicopter', MIT-LIDS Report 2003, LIDS-P-2580,
    3. 3)
      • Aircraft control and simulation
    4. 4)
      • Altug, E., Ostrowski, J.P., Mahony, R.: `Control of a quadrotor helicopter using visual feedback', IEEE Int. Conf. Robotics and Automation, 2002, Washington, DC
    5. 5)
      • Bijnens, B., Chu, Q.P., Voorsluijs, G.M., Mulder, J.A.: `Adaptive feedback linearization flight control for a helicopter UAV', AIAA Guidance, Navigation, and Control Conf. and Exhibit, 2005, San Francisco, CA
    6. 6)
      • Madani, T., Benallegue, A.: `Backstepping control for a quadrotor helicopter', Proc. 2006 IEEE/RSJ Int. Conf. Intelligent Robots and Systems, 2006, Bejing, China
    7. 7)
      • Mistler, V., Benallegue, A., M'Sirdi, N.K.: `Exact linearization and non-interacting control of a-4 rotors helicopter via dynamic feedback', 10thIEEE Int. Workshop on Robot–Human Interactive Communication, 2001, Paris
    8. 8)
      • Exact linearization and sliding mode observer for a quadrotor unmanned aerial vehicle
    9. 9)
      • Modelling and control of mini flying machines
    10. 10)
    11. 11)
      • Nonlinear systems
    12. 12)
      • Applied nonlinear control
    13. 13)
    14. 14)
      • Prasad, J.V.R., Calise, A.J.: `Adaptive nonlinear controller synthesis and flight evaluation on an unmanned helicopter', Proc. 1999 IEEE Int. Conf. Control Applications, 1999, Kohala Coast-Island of Hawaii, USA
    15. 15)
      • Calise, A.J., Kim, B.S., Leitner, J., Prasad, J.V.R.: `Helicopter adaptive flight control using neural networks', Proc. 33rd Conf. Decision and Control, 1994, Lake Buena Vista, FL
    16. 16)
      • Adaptive output feedback control of a class of nonlinear systems using neural networks
    17. 17)
    18. 18)
      • Nonlinear adaptive control of agile anti-air missiles using neural networks
    19. 19)
      • Campos, J., Lewis, F.L., Selmic, C.R.: `Backlash compensation in discrete time nonlinear systems using dynamic inversion by neural networks', Proc. 2000 IEEE Int. Conf. Robotics and Automation, 2000, San Francisco, CA
    20. 20)
    21. 21)
      • Bouabdallah, S., Noth, A.E., Siegwart, R.: `PID vs LQ control techniques applied to an indoor micro quadrotor', Int. Conf. Intelligent Robots and Systems, 2004, Sendai, Japan, (IEEE, p. 2451–2456
    22. 22)
      • Neural network control of robot manipulators and nonlinear systems
    23. 23)
    24. 24)
      • The coordination of arm movements: an experimentally confirmed mathematical model
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cta_20080002
Loading

Related content

content/journals/10.1049/iet-cta_20080002
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address