Hybrid controller using a neural network for a PM synchronous servo-motor drive

A permanent magnet (PM) synchronous servo-motor drive with a hybrid controller, which combines the advantages of the integral-proportional (IP) controller and the neural network, is introduced for both speed and position control. First, the IP speed and position controllers are designed according to the estimated plant model to match the time-domain command tracking specifications. Then the resulting closed-loop tracking transfer function of the speed-control system is used as the reference model, and an adaptive signal generated from the neural-network controller, whose connective weights are trained on-line using the proposed delta adaptation law according to the model-following error of the outputs, is added to the speed-control system to preserve a favourable model-following characteristic under various operating conditions. To demonstrate the effectiveness of the proposed hybrid controller, the control scheme is also implemented for the position-control system