Ultrasonic motor's velocity control based on the BP fuzzy neural network with stored information

Ultrasonic motor has no precise mathematical model presently, and its output has strong time-variation and nonlinearity. A modified BP neural network controller is presented in this paper which consists of input layer, membership function layer, rule layer and output layer. Based on the traditional BP neural network theory, by adding fuzzy deviation neuron and relative neuron to the net, the rule layer receives not only the signal from the membership function layer but also the delayed output signal of itself, so it can store the past input and output information to improve the stability of the study and memory. The traveling wave ultrasonic motor's revolving speed was controlled by using the modified BP neural network controller. The emulation results reveals the control accuracy and response speed improves compared with the traditional BP neural network, and the controlling system has strong robustness to the stochastic disturbance.