An adaptive neural speed controller of a de motor is proposed. The art
ificial neural network (ANN) is trained by the online backpropagation
algorithm. The output of the ANN gives the control voltage applied to
the de motor. The difference between the reference and the actual roto
r speed of the motor is backpropagated through the ANN at each step of
the control process for updating the connection weights of the ANN. T
he control scheme requires neither a knowledge of any motor parameters
, nor preferential training of the ANN. The performance of the control
ler is simulated depending on the rotor speed noise of the motor, the
rapidity of its dynamics, the sampling period, and the sharp instantan
eous change of the load, or in the reference speed trajectory. (C) 199
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