Design of a neural fuzzy controller for induction motor speed control

The authors present a neural fuzzy controller with a PI controller for a system to control the speed of an induction motor. The design of this algorithm is based on a normal PI controller and a neural fuzzy controller that is implemented using appropriate fuzzy rules and a neural network. The neural fuzzy controller uses fuzzy rules as the training pattern of a neural network and uses the backpropagation method to adjust the weights between the neurons of the neural network in order to minimize the error between the target output and the actual output. The fuzzy rules are then recorded in the neural network. The proposed controller is applied to control the speed of the induction motor. Experimental results show that the proposed controller has transient and steady-state performance better than those of the conventional PI controllers