Position Control of Ultrasonic Motor Using Support Vector Regression

概要

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The ultrasonic motor (USM) has excellent performance and many useful features that electromagnetic type motors do not have. It has been used in many practical applications. A characteristic of the USM that is affected by friction is strong nonlinearity, which makes it difficult to control. This paper proposes a position control method for the USM using Support Vector Regression (SVR), which is a regression method for Support Vector Machines. It is a newly proposed method of machine learning that does not have the disadvantages of Neural Network such as a large number of learning times, local-minima, overfitting and so on. The proposed method uses an SVR controller combined with a PI controller. The SVR controller performs nonlinear input-output mapping of the USM. The learning of the SVR controller uses training data obtained from experiments. The effectiveness of the proposed control method is confirmed by experiments.
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