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. This dead-zone is a problem as an accurate positioning actuator for industrial applications and it is important to eliminate the deadzone in order to improve the control performance. This paper proposes a new position control scheme for ultrasonic motors to overcome dead-zone employing model reference adaptive control with dead-zone compensation with fuzzy inference. The deadzone 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.