Study On The MRAC Of Ultrasonic Motor Based On Popov Hyperstability Criterion

Ultrasonic motor has obvious nonlinear characteristic, it can obtain good control performance by using of the adaptive control method. In this paper, we study on the speed control of ultrasonic motor, the improved MIT model reference adaptive control strategy is designed. Then the complexity of the control strategy is reduced and it is advantage to the industrialization of ultrasonic motor. The model reference adaptive control strategy is designed on the basis of Popov’s hyperstability criterion, the control precision is tried to be improved and it provides the key foundational parts for the high precision motion control applications.The cost of ultrasonic motor control system including the driving circuit can be reduced by using a relatively simple motion control algorithm, so as to promote the mass production of ultrasonic motor. Based on this purpose, the improved MIT model reference adaptive control strategy of ultrasonic motor is designed, the adaptive law is derived by the gradient method. This strategy makes the design of the reference model doesn’t rely on the model of ultrasonic motor, the contradiction between the form of the reference model and the expectation of the MIT control is solved. Further, in order to guarantee the stability of system, an improved MIT speed control strategy is presented, the adaptive law is derived by the Lyapunov stability theory. Experiments show that these two kinds of control strategies are feasible, the algorithms are simple, the amounts of online calculation are small and the control effects are good.Then, the Popov’s hyperstability criterion is used to design the model reference adaptive control strategy of ultrasonic motor. The differential feedback network based on the values of input and output is used to control the speed of ultrasonic motor. The simulation shows that the proposed control strategy is effective. In order to improve the anti-interference performance of system, state variable filter is added based on the method of differential feedback network. The simulation shows that the speed control performance is improved further.