Abstract
Considers position control of a PM stepper motor. A control scheme is proposed based on a kind of exact linearization controller and a neural network based compensating controller. This scheme takes advantage of the simplicity of the model based control approach and uses the neural network controller to compensate for the motor modeling uncertainties. The neural network is trained online based on Lyapunov theory and thus its convergence is guaranteed.
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