Position control of ultrasonic motors using MRAC and dead-zone compensation with fuzzy inference

The ultrasonic motor has a heavy nonlinearity, which varies with driving conditions and possesses variable dead-zone in the control input associated with applied load torque. The dead-zone is a problem as an accurate positioning actuator for industrial applications and it is important to eliminate the dead-zone in order to improve the control performance. This paper proposes a new position control scheme of ultrasonic motors to overcome dead-zone employing model reference adaptive control with fuzzy inference. The dead-zone is compensated by fuzzy inference, whereas model reference adaptive control performs accurate position control. Mathematical models are formulated and experimental results are given to validate the proposed position control scheme.