Abstract
Piezoelectric actuators (PEA) are frequently employed in applications where nano-Micr-odisplacement is required because of their high-precision performance. However, the positioning is affected substantially by the hysteresis which resembles in an nonlinear effect. In addition, hysteresis mathematical models own deficiencies that can influence on the reference following performance. The objective of this study was to enhance the tracking accuracy of a commercial PEA stack actuator with the implementation of a novel approach which consists in the use of a Super-Twisting Algorithm (STA) combined with artificial neural networks (ANN). A Lyapunov stability proof is bestowed to explain the theoretical solution. Experimental results of the proposed method were compared with a proportional-integral-derivative (PID) controller. The outcomes in a real PEA reported that the novel structure is stable as it was proved theoretically, and the experiments provided a significant error reduction in contrast with the PID.
Highlights
In the early 1970s, the high accuracy positioning was constrained only at academic domains; as a result of advanced fabrication methods, the beginning of the current century leads the possibility of bringing micro-actuators in industrial environments [1].Piezoelectric actuators (PEAs) are suitable candidates when there is an application that needs for nano-microdisplacement combined with precision as requirements [2]
This research was based on commercial hardware from Thorlabs where the PEA used was a PK4FYC2, which is a stack actuator that consists of numerous piezoelectric chips stuck with epoxy and glass beads
The training of the artificial neural networks (ANN) was undertaken with data recorded from the triangle input signal described in Section 2.1, which has an amplitude of 145 V and 4 s of a period
Summary
Piezoelectric actuators (PEAs) are suitable candidates when there is an application that needs for nano-microdisplacement combined with precision as requirements [2]. These systems provide accuracy and mechanical capabilities due to their high stiffness [3]. The blend is produced with the advantage of their size, which is an asset for the downsizing trend in actuators today. Due to these benefits, the applications are broad which includes energy harvesting [4], active vibration [5], motor design [6], etc. In recent years, the PEA has been a research aim for medical uses, such as drug delivery systems [7], micro grippers [8], spinal injection device [9], and orthodontic treatment [10]
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