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Observation of stage position in a two-axis nano-positioner using hybrid Kalman filter

Bayat, S ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.24200/sci.2021.54441.3752
  3. Publisher: Sharif University of Technology , 2021
  4. Abstract:
  5. This study presents a novel method for observation of stage position in a 2D nano-positioning system based on a hybrid Kalman filter. The proposed method obviates the need to measure the stage position directly using complex and costly capacity sensors. Instead, traditional piezo actuators equipped with strain gauge sensors are utilized to measure the deection of the magnification system at the position of actuators. Then, a powerful estimation algorithm called Kalman filter was employed to observe stage displacements. The designed hybrid Kalman filter uses dynamical equations of motion in the prediction step. The piezo actuators deections are measured and exploited to correct the predicted values for the system state variables. In order to simulate realistic conditions, a relatively exact COMSOL model was developed for the nano-positioner. Here, the noise was added to the piezo displacements obtained by simulating this model, and these noisy data were used as measurements in the Kalman filter algorithm. The designed hybrid Kalman filter was examined for three different updating time steps. The results showed that the designed Kalman filter appropriately estimated the stage displacements, and its accuracy was enhanced upon reducing the filter time step. © 2021 Sharif University of Technology
  6. Keywords:
  7. Actuators ; Equations of motion ; Genetic algorithms ; Nanotechnology ; Strain gages ; Nano-positioner ; Nano-positioning ; Nano-positioning stages ; Novel methods ; Observer ; Piezo actuator ; Positioning system ; System-identification ; Time step ; Two-axis ; Kalman filters ; hybrid ; Kalman filter ; noise ; positioning system ; sensor
  8. Source: Scientia Iranica ; Volume 28, Issue 5 B , 2021 , Pages 2628-2638 ; 10263098 (ISSN)
  9. URL: http://scientiairanica.sharif.edu/article_22456.html