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Dynamic Structure Networks for Stable Adaptive Control

  • Simon G. Fabri
  • Visakan Kadirkamanathan
Part of the Communications and Control Engineering book series (CCE)

Abstract

The local representation properties and the possibility of predetermining the basis function parameters in Gaussian RBF networks, makes them ideal candidates for implementing functional adaptive control. However these attractive features are somewhat tarnished by the curse of dimensionality problem associated with GaRBF networks when used for high dimensional spaces.

Keywords

Radial Basis Function Tracking Error Radial Basis Function Neural Network Mesh Point Tracking Accuracy 
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-Verlag London 2001

Authors and Affiliations

  • Simon G. Fabri
    • 1
  • Visakan Kadirkamanathan
    • 2
  1. 1.Department of Electrical Power and Control EngineeringUniversity of MaltaMsidaMalta
  2. 2.Department of Automatic Control and Systems EngineeringThe University of SheffieldSheffieldEngland

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