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Direct Adaptive Neuro Flight Controller Using Fully Tuned RBFN

  • N. Sundararajan
  • P. Saratchandran
  • Yan Li
Chapter
Part of the The Springer International Series on Asian Studies in Computer and Information Science book series (ASIS, volume 12)

Abstract

Control laws and design methods incorporating ANNs have been intensively studied in the area of aircraft flight control. In [17], Calise et al. have summarized some current research efforts of applying NN technology for flight control system design, with emphasis on nonlinear adaptive control. It has been shown that NN with on-line learning can adapt to aircraft dynamics which is poorly known or rapidly changing. However, in most of these applications, feedforward network with BP learning algorithm or its extensions has been the main paradigm, and there are only limited papers which explore the application of RBFN.

Keywords

Hide Neuron Radial Basis Function Neural Network Flight Control Proportional Controller Tuning Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • N. Sundararajan
    • 1
  • P. Saratchandran
    • 1
  • Yan Li
    • 1
  1. 1.Nanyang Technological UniversitySingapore

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