Journal article 661 views 478 downloads
A Neural-Network-Based Controller for Piezoelectric-Actuated Stick–Slip Devices
Long Cheng,
Weichuan Liu,
Chenguang Yang,
Tingwen Huang,
Zeng-Guang Hou,
Min Tan
IEEE Transactions on Industrial Electronics, Volume: 65, Issue: 3, Pages: 2598 - 2607
Swansea University Author: Chenguang Yang
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DOI (Published version): 10.1109/TIE.2017.2740826
Abstract
Piezoelectric-actuated stick-slip device (PASSD) is a highly promising equipment that composed of one end-effector, one piezoelectric actuator (PEA) and one driving object adhered to the PEA. Since the end-effector can slip on the surface of the driving object, the PASSD is capable of realizing the...
| Published in: | IEEE Transactions on Industrial Electronics |
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| ISSN: | 0278-0046 1557-9948 |
| Published: |
2018
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa34959 |
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| Abstract: |
Piezoelectric-actuated stick-slip device (PASSD) is a highly promising equipment that composed of one end-effector, one piezoelectric actuator (PEA) and one driving object adhered to the PEA. Since the end-effector can slip on the surface of the driving object, the PASSD is capable of realizing the macro-level motion with the micro-level precision. Due to the following two reasons: (1) the complicated relative motion between the end-effector and the driving object, and (2) the inherent hysteresis nonlinearity in the PEA, the ultraprecision displacement control of the end-effector of PASSDs raises a real challenge. Towards solving this challenge, a neural network based controller is proposed in this paper. First, a neural network based model is proposed to capture the relative motion between the end-effector and the driving object. Second, a neural network based inversion model is developed to on-line calculate the desired position of the PEA under the predesigned reference of the end-effector. Third, a dynamic linearized neural network based model predictive control method, which can effectively handle the hysteresis nonlinearity, is employed to implement the displacement control of the PEA, which finally results in an overall high-precision controller of the end-effector. Finally, a PASSD prototype has been implemented and tested through experimental studies to demonstrate the effectiveness of the proposed approach. |
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| Keywords: |
Stick-slip, piezoelectric actuator, endeffector, neural network |
| College: |
Faculty of Science and Engineering |
| Issue: |
3 |
| Start Page: |
2598 |
| End Page: |
2607 |