Adaptive nonlinear control of agile antiair missiles using neural networks

  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.},
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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