Adaptive speed control for induction motor drives using neural networks

In this paper, the adaptive speed control of induction motor drives using neural networks is presented. To obtain good performances both in tracking and regulating characteristics, a digital two-degree-of-freedom (2DOF) controller and its quantitative design procedure are proposed. The parameters of the controller corresponding to various drive parameter sets are found off-line and stored as the training patterns. Under normal operation, the true drive parameters are real-time identified and they are converted into the controller parameters through multilayer forward computation by neural networks. In which, the connection weights of the multilayer feedforward network are estimated by backpropagation learning algorithm