Adaptive slip frequency control system based on neural networks identification for induction motor

An adaptive slip frequency control system is designed for induction motor in order to solve the problem of poor control accuracy under the conditions of low speed in vector control. BP network is used as nonlinear identification to improve identification accuracy of drive system. Position controller and speed controller are realized by single neuron learning algorithms to increase the speed control accuracy of vector control. Furthermore, the stability of adaptive slip frequency control system is improved through self-learning abilities of neural networks. Simulation results have shown that the adaptive slip frequency control system based on neural networks identification is provided with better adaptability and stronger stability compared with PID control system.