Position control of ultrasonic motor using PID-IMC combined with neural network based on probability

Issue title: ICMIT2011

Guest editors: Kazuhiko Takahashi and Minoru Sasaki

Article type: Research Article

Authors: Mu, Shenglin^{a; *} | Tanaka, Kanya^a

Affiliations: [a] Graduate School of Science and Engineering, Yamaguchi University, Yamaguchi, Japan | Doshisha University, Kyoto, Japan | Department of Human and Information Systems, Faculty of Engineering, Gifu University, Gifu, Japan

Correspondence: [*] Corresponding author: Shenglin Mu, Graduate School of Science and Engineering, Yamaguchi University, 2-16-1 Tokiwadai, Ube, Yamaguchi, Japan. Tel.: +81 836 858 445; Fax: +81 836 859 401; E-mail: p002we@yamaguchi-u.ac.jp

Abstract: In this paper, a novel control scheme of PID type internal model control (PID-IMC) using neural network (NN) is proposed for the position control of ultrasonic motor (USM). In the proposed scheme, a new NN controller combined with particle swarm optimization (PSO) based on probability is introduced. The NN controller is employed for tuning the control parameter in PID-IMC for compensating the characteristic changes and non-linearity in USM. On one hand, the application of the proposed method avoids the Jacobian estimation in conventional back-propagation (BP) type NN. On the other hand, the PSO based on probability, originated from tribes-PSO, simplifies the PSO setting by reducing the parameters to be set in USM control. For confirming the effectiveness of the proposed method in position control, a group of experiments have been done on an existent USM servo system and the results are studied in this paper.

Keywords: Ultrasonic motor, PID-IMC, neural network, particle swarm optimization

DOI: 10.3233/JAE-121626

Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 41, no. 1, pp. 59-71, 2013