Abstract
Based on the experimental data of an ultrasonic motor's dynamic response, the non-linear Hammerstein model of an ultrasonic motor driving system is obtained by using particle swarm optimization. This model uses motor-driven frequency as input and rotating speed as output. As such, the main characteristics of nonlinearity in the ultrasonic motor operation process can better be expressed with a relatively simple form and a kind of feasible modeling method for model identification of ultrasonic motor system is proposed. Based on this Hammerstein model, the self-tuning nonlinear generalized predictive speed control strategy of an ultrasonic motor is proposed and the tuning method of the controller's parameters is also discussed in detail. This control strategy utilizes the roll forecasting, optimization and online self-tuning methods to deal with the nonlinearity of the ultrasonic motor. The experiments with a variety of disturbances indicate the efficiency and robustness of the proposed strategy.
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