DocumentCode :
606757
Title :
IMC-based feedforward control of a piezoelectric tube actuator
Author :
Mohammadzaheri, M. ; Grainger, Steven ; Kopaei, M.K. ; Bazghaleh, M.
Author_Institution :
Sch. of Mech. Eng., Univ. of Adelaide, Adelaide, SA, Australia
fYear :
2013
fDate :
2-5 April 2013
Firstpage :
357
Lastpage :
361
Abstract :
This article addresses sensorless control of a piezoelectric tube actuator to avoid the expense and practical limits of displacement sensors in nanopositioning. Three electrical signals have been used to estimate displacement: the piezoelectric voltage, the induced voltage and the sensing voltage. In this work, the piezoelectric voltage was employed to estimate displacement which does not require drift removal like the sensing voltage and does not suffer from a time lag respect to displacement like the induced voltage. This signal is the actuating signal at the same time, so the sensorless control system is feedforward. It was shown the relationship between the piezoelectric actuator and displacement is nearly linear at the designated operation area: excitation of the tube by triangular voltage functions with the magnitude up to 60V and the frequency up to 60Hz. Therefore, Internal Model Control (IMC) was employed to design this feedforward controller based on a second order linear discrete model which maps the piezoelectric voltage into displacement. The performance of the proposed feedforward controller has been compared with a well-tuned feedforward P-action controller and a remarkable improvement has been observed.
Keywords :
control system synthesis; feedforward; nanopositioning; piezoelectric actuators; sensorless machine control; sensors; IMC-based feedforward control; displacement estimation; displacement sensors; internal model control; nanopositioning; piezoelectric tube actuator; piezoelectric voltage; sensorless control; Electron tubes; Feedforward neural networks; Microscopy; Piezoelectric actuators; Sensors; Transfer functions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Sensors, Sensor Networks and Information Processing, 2013 IEEE Eighth International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-5499-8
Type :
conf
DOI :
10.1109/ISSNIP.2013.6529816
Filename :
6529816
Link To Document :
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