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A Model Deviation Correction Method Based on Iterative Learning for Ultrasonic Motor

Wenwen Huang and Jingzhuo Shi*
International Journal of Control, Automation, and Systems, vol. 20, no. 11, pp.3799-3807, 2022

Abstract : Most control strategies are designed based on the mathematical model of the controlled object. The consistency between the mathematical model and the actual object is the necessary prerequisite to ensure that the actual control performance meets the expectation. In order to make the actual control performance entirely consistent with the expectation expressed by the simulation results, taking the ultrasonic motor control system as an example, a new nonlinear model correction method is proposed. The proposed method generates the timevarying correction of control variable through a simple P-type iterative learning process, so that the response process of the actual system is consistent with the simulation results expressing desired control performance. The direct target of this method is the control performance, and the estimated result is the inverse function of the nonlinear characteristics of the plant. The inverse model is connected in series with the real object, so that the dynamic performance of the actual system is consistent with the designed performance. Comparative experiment results show the effectiveness of the proposed method.

Keyword : "Estimation, identification, inverse model, iterative learning control (ILC). "

 
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