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Neural Networks-Based PID Precision Motion Control of a Piezo-Actuated Microinjector

  • Yizheng Yan
  • Qingsong XuEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11745)

Abstract

Piezoelectric actuators are widely employed in the field of micro-/nanomanipulation. However, hysteresis is the dominant issue in piezoelectric actuators, which leads to a great challenge to achieve high precision micromanipulation. Proportional-integral-derivative (PID) control is an efficient approach to reduce hysteresis effect in piezoelectric actuators. However, its parameter tuning is a time-consuming work for PID motion tracking control implementation. In this work, the neural networks (NN) is adopted to provide a functional model for PID with optimized parameters. It enables an intelligent and adaptive motion tracking process. The effectiveness of the presented NN-based PID control scheme is verified by performing simulation studies.

Keywords

Piezoelectric actuator Hysteresis PID control Neural networks Precision motion control 

Notes

Acknowledgement

This work was supported in part by the National Natural Science Foundation of China under Grant 51575545, the Macao Science and Technology Development Fund under Grant 179/2017/A3, and Research Committee of the University of Macau under Grant MYRG2018-00034-FST.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Electromechanical Engineering, Faculty of Science and TechnologyUniversity of MacauMacauChina

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