Adaptive control of large induction motors with highly nonlinear loads using neural networks

The authors present an approach for adaptive speed control of large induction motors by means of electric frequency variations. In the proposed method, the equations and the parameters of the motor and load are considered unknown. An adaptive scheme, with feedforward neural networks, is used to estimate a function that is applied as feedback. The neural network is trained in two sessions: offline and online phases. Preliminary results showed that the method is able to identify and control the system, considering the motor and load nonlinearities. The method is adaptive since, during normal operation, some backpropagation steps can be applied to take into account some possible variations in the motor and load parameters