Hysteresis modelling and feedforward compensation of piezoelectric nanopositioning stage with a modified Bouc-Wen model
- Author(s): Min Ming 1 ; Zhao Feng 1 ; Jie Ling 1 ; Xiao-Hui Xiao 1
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View affiliations
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Affiliations:
1:
School of Power and Mechanical Engineering , Wuhan University , Wuhan 430072 , People's Republic of China
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Affiliations:
1:
School of Power and Mechanical Engineering , Wuhan University , Wuhan 430072 , People's Republic of China
- Source:
Volume 13, Issue 8,
August
2018,
p.
1170 – 1174
DOI: 10.1049/mnl.2017.0793 , Online ISSN 1750-0443
© The Institution of Engineering and Technology
Received
13/11/2017,
Accepted
25/04/2018,
Revised
22/03/2018,
Published
01/08/2018
Piezoelectric actuators (PEAs) are widely applied in various nanopositioning equipment. However, the strong hysteresis nonlinearity compromises the positioning accuracy. In this work, a novel modified Bouc-Wen (MBW) model with a polynomial function of the differential of the input is established for modelling the hysteresis nonlinearity of the PEA-actuated nanopositioning stages. The particle swarm optimisation algorithm is adopted to identify the parameters of the MBW model with a set of input–output experimental data. The obtained model with the corresponding identification parameters matches well the experimental data with 0.31% relative error. A feedforward compensator based on the obtained model is also applied to compensate the hysteresis nonlinearity. Experiments are conducted to validate the effectiveness of this approach, and the results show the great improvement of positioning accuracy of the stage.
Inspec keywords: nanopositioning; hysteresis; piezoelectric actuators; vibration control; feedforward; control nonlinearities; compensation; position control; particle swarm optimisation
Other keywords: piezoelectric nanopositioning stage; experimental data; 0.31% relative error; modified Bouc; positioning accuracy; piezoelectric actuators; strong hysteresis nonlinearity; feedforward compensation; MBW model; input–output; particle swarm optimisation algorithm; feedforward compensator; (MBW) model; nanopositioning equipment; corresponding identification parameters; PEA; polynomial function
Subjects: Spatial variables control; Piezoelectric devices; Optimisation techniques; Control system analysis and synthesis methods; Nonlinear control systems; Control technology and theory (production); Electric actuators and final control equipment
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