Position control of ultrasonic motors using dead-zone compensation with fuzzy neural network

The ultrasonic motor has nonlinear characteristics, which vary with driving conditions and possess variable dead-zone in the control input that is associated with the applied load torque. The dead-zone has a problem in accurate positioning actuator. To improve the control performance of the ultrasonic motor, the dead-zone nonlinearity should be eliminated. This article proposes a new position control scheme for the ultrasonic motors that eliminates the problem due to dead-zone by employing fuzzy neural network (FNN). To achieve the accurate position control when drive conditions vary, FNN can adjust the membership function for the antecedent part. The training of FNN is achieved using online backpropagation algorithm. The dead-zone is compensated by FNN, and PI controller performs the accurate positioning of the drive system. The validity of the proposed method is confirmed by experimental results.