Journal
ACTUATORS
Volume 11, Issue 5, Pages -Publisher
MDPI
DOI: 10.3390/act11050122
Keywords
hysteresis characteristics; Duhem model; segment identification; artificial fish swarm algorithm; composite controller
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This study proposed an improved hysteresis model and composite controller based on a hybrid intelligent optimization algorithm, which achieved good results in experiments and improved the positioning accuracy of the platform.
The hysteresis characteristic of piezoelectric micro-positioning platforms seriously affects its positioning accuracy in precision positioning. It is important to design an effective hysteresis model and control scheme. Based on the analysis of the Duhem model, this paper proposes to divide the hysteresis curve into two parts, the step-up section and the step-down section, to identify the model parameters, respectively, and a hybrid intelligent optimization algorithm based on the artificial fish swarm algorithm and the bat algorithm is proposed. The simulation experiment verified that the error of the improved model was reduced by 48.97%, which greatly improved the identification accuracy of the Duhem model. Finally, an inverse model of the Duhem model for the segmental identification of the improved artificial fish swarm algorithm is established, and a composite controller integrating feedforward, feedback and decoupling control is designed on the basis of the inverse model, and an experimental verification is carried out. The results show that the displacement errors of the composite controller under different voltage signals are all within 0.25%. Therefore, the established model can accurately express the hysteresis characteristics of the platform, and the use of the composite controller can effectively reduce the accuracy error caused by the hysteresis characteristics.
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