Radial basis neural network adaptive controller for servomotor

Neuro controllers have recently been applied to practical systems. The commonest network in these applications has been the multilayer perceptron trained by backpropagation. The objective of this paper is to present a new neuro control scheme for servomotors. An important feature of the proposed control scheme is that the radial basis function network, instead of normal backpropagation neural net, is used to tune a conventional controller. Another goal is to introduce a two layer radial basis network structure to be trained with the novel algorithm. Simulations are performed with both radial basis function networks showing that the proposed neuro controller can be trained in a short period of time and is robust.