Journal of Applied Mathematics

  • J. Appl. Math.
  • Volume 2013, Special Issue (2013), Article ID 452653, 12 pages.

Adaptive Neural Network Dynamic Inversion with Prescribed Performance for Aircraft Flight Control

Wendong Gai, Honglun Wang, Jing Zhang, and Yuxia Li

Full-text: Open access

Abstract

An adaptive neural network dynamic inversion with prescribed performance method is proposed for aircraft flight control. The aircraft nonlinear attitude angle model is analyzed. And we propose a new attitude angle controller design method based on prescribed performance which describes the convergence rate and overshoot of the tracking error. Then the model error is compensated by the adaptive neural network. Subsequently, the system stability is analyzed in detail. Finally, the proposed method is applied to the aircraft attitude tracking control system. The nonlinear simulation demonstrates that this method can guarantee the stability and tracking performance in the transient and steady behavior.

Article information

Source
J. Appl. Math., Volume 2013, Special Issue (2013), Article ID 452653, 12 pages.

Dates
First available in Project Euclid: 14 March 2014

Permanent link to this document
https://projecteuclid.org/euclid.jam/1394806107

Digital Object Identifier
doi:10.1155/2013/452653

Zentralblatt MATH identifier
06950684

Citation

Gai, Wendong; Wang, Honglun; Zhang, Jing; Li, Yuxia. Adaptive Neural Network Dynamic Inversion with Prescribed Performance for Aircraft Flight Control. J. Appl. Math. 2013, Special Issue (2013), Article ID 452653, 12 pages. doi:10.1155/2013/452653. https://projecteuclid.org/euclid.jam/1394806107


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References

  • S. A. Snell, D. F. Enns, and W. L. Garrard Jr., “Nonlinear inversion flight control for a supermaneuverable aircraft,” Journal of Guidance, Control, and Dynamics, vol. 15, no. 4, pp. 976–984, 1992.
  • D. Enns, D. Bugajski, R. Hendrick, and G. Stein, “Dynamic inversion: an evolving methodology for flight control design,” International Journal of Control, vol. 59, no. 1, pp. 71–91, 1994.
  • J. Leitner, A. Calise, and J. V. R. Prasad, “Analysis of adaptive neural networks for helicopter flight control,” Journal of Guidance, Control, and Dynamics, vol. 20, no. 5, pp. 972–979, 1997.
  • R. Rysdyk and A. J. Calise, “Robust nonlinear adaptive flight control for consistent handling qualities,” IEEE Transactions on Control Systems Technology, vol. 13, no. 6, pp. 896–910, 2005.
  • C. Cao and N. Hovakimyan, “Design and analysis of a novel ${L}_{1}$ adaptive control architecture with guaranteed transient performance,” IEEE Transactions on Automatic Control, vol. 53, no. 2, pp. 586–591, 2008.
  • W. Gai, H. Wang, and D. Li, “Trajectory tracking for automated aerial refueling based on adaptive dynamic inversion,” Journal of Beijing University of Aeronautics and Astronautics, vol. 38, no. 5, pp. 585–590, 2012 (Chinese).
  • H. Xu and P. A. Ioannou, “Robust adaptive control for a class of MIMO nonlinear systems with guaranteed error bounds,” IEEE Transactions on Automatic Control, vol. 48, no. 5, pp. 728–742, 2003.
  • V. Stepanyan and K. Krishnakumar, “Adaptive control with reference model modification,” Journal of Guidance, Control, and Dynamics, vol. 35, no. 4, pp. 1370–1374, 2012.
  • C. P. Bechlioulis and G. A. Rovithakis, “Adaptive control with guaranteed transient and steady state tracking error bounds for strict feedback systems,” Automatica, vol. 45, no. 2, pp. 532–538, 2009.
  • C. P. Bechlioulis and G. A. Rovithakis, “Prescribed performance adaptive control for multi-input multi-output affine in the control nonlinear systems,” IEEE Transactions on Automatic Control, vol. 55, no. 5, pp. 1220–1226, 2010.
  • A. Kostarigka and G. Rovithakis, “Adaptive dynamic output feedback neural network control of uncertain MIMO nonlinear systems with prescribed performance,” IEEE Transactions on Neural Networks and Learning Systems, vol. 23, no. 1, pp. 138–149, 2012.
  • C. P. Bechlioulis, Z. Doulgeri, and G. A. Rovithakis, “Guaranteeing prescribed performance and contact maintenance via an approximation free robot force/position controller,” Automatica, vol. 48, no. 2, pp. 360–365, 2012.
  • M. L. Fravolini, A. Ficola, G. Campa, M. R. Napolitano, and B. Seanor, “Modeling and control issues for autonomous aerial refueling for UAVs using a probe-drogue refueling system,” Aerospace Science and Technology, vol. 8, no. 7, pp. 611–618, 2004.
  • J. P. Nalepka and J. L. Hinchman, “Automated aerial refueling: extending the effectiveness of unmanned air vehicles,” in Proceedings of the AIAA Modeling and Simulation Technologies Conference and Exhibit, pp. 240–247, August 2005, AIAA Paper 2005-6005.
  • Y. Xili, F. Yong, and Z. Jihong, “Transition flight control of two vertical/short takeoff and landing aircraft,” Journal of Guidance, Control, and Dynamics, vol. 31, no. 2, pp. 371–385, 2008.
  • W. Gai and H. Wang, “Closed-loop dynamic control allocation for aircraft with multiple actuators,” Chinese Journal of Aeronautics, vol. 26, no. 3, pp. 676–686, 2013.
  • B. Stevens and L. Lewis, Aircraft Control and Simulation, Wiley, New York, NY, USA, 2nd edition, 2003.
  • B. S. Kim and A. J. Calise, “Nonlinear flight control using neural networks,” Journal of Guidance, Control, and Dynamics, vol. 20, no. 1, pp. 26–33, 1997.
  • W. Wang and C. Wen, “Adaptive actuator failure compensation control of uncertain nonlinear systems with guaranteed transient performance,” Automatica, vol. 46, no. 12, pp. 2082–2091, 2010.
  • R. T. Rysdyk and A. J. Calise, “Adaptive model inversion flight control for tilt-rotor aircraft,” Journal of Guidance, Control, and Dynamics, vol. 22, no. 3, pp. 402–407, 1999.