Hybrid Model Based on Maxwell-Slip Model and Relevance Vector Machine

This article proposes a hybrid model based on Maxwell-slip (MS) model and relevance vector machine (RVM) for piezoelectric actuators (PEAs). The MS model maps the input voltage into the internal state space and provides an estimation of the output displacement. The output function of the MS model pr...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 2021-10, Vol.68 (10), p.10050-10057
Main Authors: Liu, Yanfang, She, Jiayu, Duan, Haiyan, Qi, Naiming
Format: Article
Language:English
Subjects:
Asymmetry
Computational efficiency
Computational modeling
Computing time
Data points
Displacement
Hybrid model
Hysteresis
Integrated circuit modeling
Load modeling
Machine learning
Maxwell-slip (MS) model
Model accuracy
piezoelectric actuator (PEA)
Piezoelectric actuators
Random excitation
relevance vector machine (RVM)
Silicon
Slip
Strain
Tracking errors
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Summary:This article proposes a hybrid model based on Maxwell-slip (MS) model and relevance vector machine (RVM) for piezoelectric actuators (PEAs). The MS model maps the input voltage into the internal state space and provides an estimation of the output displacement. The output function of the MS model provides a linear relationship between the deformation vector and the output displacement. Replacing the regression function of the RVM by the output function of the MS model enables the RVM to update parameters of the MS model. The RVM is chosen since it is also able to provide the distribution of the estimated output displacement. Integration of the MS model with the RVM also reduces the dimension of the RVM from the number of support data points to the number of MS elements, which will reduce the computational time. Results demonstrate that the hybrid model is capable of describing rate-dependent and asymmetric hysteresis, is robust to excitations, enhances the accuracy of the MS model, and requires much shorter computational time than the standalone RVM. The modeling error under random excitation is 0.54% and for asymmetric hysteresis in a reluctance actuator is 0.31%. Compensation for hysteresis is carried out by connecting the inverse model in serial with a PEA and achieves tracking error of less than 0.81%.
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2020.3029471