Adaptive fuzzy-neuro controller for speed of wound rotor induction motor with slip energy recovery

In this paper, the authors proposed an adaptive fuzzy-neuro controller to control the speed of a wound rotor induction motor with slip energy recovery. An adaptive fuzzy-neuro controller has been designed by integrating two neural network models with a basic fuzzy logic controller. Using the backpropagation algorithm, the first neural network is trained as a plant emulator and the second neural network is used as a compensator for the basic fuzzy controller to improve its performance online. The function of the neural network plant emulator is to provide the correct error signal at the output of the neural fuzzy compensator without the need for any mathematical modeling of the plant. The scheme is applied to the control of the speed of the wound rotor induction motor process. Simulation and experimental results show that the adaptive fuzzy-neuro controller gives constant speed and good transient response without overshoot