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.
CITATION STYLE
Yan, Y., & Xu, Q. (2019). Neural networks-based PID precision motion control of a piezo-actuated microinjector. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11745 LNAI, pp. 407–418). Springer Verlag. https://doi.org/10.1007/978-3-030-27529-7_35
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