Adaptive nonlinear control of agile antiair missiles using neural networks

@article{McFarland2000AdaptiveNC,
  title={Adaptive nonlinear control of agile antiair missiles using neural networks},
  author={Michael B. McFarland and Anthony J. Calise},
  journal={IEEE Trans. Contr. Sys. Techn.},
  year={2000},
  volume={8},
  pages={749-756}
}
Research has shown that neural networks can be used to improve upon approximate dynamic inversion controllers in the case of uncertain nonlinear systems. In one possible architecture, the neural network adaptively cancels linearization errors through on-line learning. Learning may be accomplished by a simple weight update rule derived from Lyapunov theory, thus assuring the stability of the closed-loop system. In this paper, the authors discuss the evolution of this methodology and its… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 13 references

Nonlinear flight control using neural networks

  • B. S. Kim, A. J. Calise
  • AIAA J., vol. 20, pp. 26–33, Jan.–Feb. .
  • 1997
Highly Influential
5 Excerpts

Agile missile dynamics and control

  • K. A. Wise, D. J. Broy
  • Proc. AIAA Guidance Navigation Contr. Conf. , San…
  • 1996
1 Excerpt

Neural-adaptive nonlinear autopilot design for an agile anti-air missile

  • presented at the AIAA Guidance Navigation Contr…
  • 1996
1 Excerpt