NDLI: Predictive Control of Traveling Wave Ultrasonic Motors using neural network

Content Provider	IEEE Xplore Digital Library
Author	Ahmadi, M. Mojallali, H. Fotovvati, M.H.
Copyright Year	2011
Description	Author affiliation: Department of Electrical engineering, University of Guilan, Rasht, Iran (Ahmadi, M.; Mojallali, H.; Fotovvati, M.H.)
Abstract	Traveling Wave Ultrasonic Motors (TWUSMs) possess extreme nonlinear properties such as saturation reverse effect and dead-zone, which are reliant on the driving conditions. These characteristics make modeling and control of TWUSMs highly challenging. Thus, deriving a simple and precise mathematical model suitable for controlling USMs has been a major problem for researchers. In this paper, a multi-layer perception neural network (MLPNN) based on the Hammerstein structure of TWUSMs is utilized to annul the nonlinear subsystem of TWUSM. Subsequently, a Generalized Predictive Controller (GPC), along with the inverse model characterized by MLPNN, is utilized to control the angular position of a TWUSM. The inverse model is able to cover all the variations in initial conditions, load torque, and the driving frequency. Simulation results based on the proposed scheme are presented which validate the scheme's performance.
Starting Page	256
Ending Page	261
File Size	803596
Page Count	6
File Format	PDF
ISBN	9781612844220
e-ISBN	9781612844213
DOI	10.1109/PEDSTC.2011.5742428
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-02-16
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Hammerstein Model Ultrasonic Motor Torque Neural Network Neurons Rotors Artificial neural networks Acoustics Generalized Predictive Control Mathematical model Load modeling
Content Type	Text
Resource Type	Article

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