Feedforward Compensation Analysis of Piezoelectric Actuators Using Artificial Neural Networks with Conventional PID Controller and Single-Neuron PID Based on Hebb Learning Rules

Cristian Napole,Oscar Barambones,Javier Velasco,Isidro Calvo

doi:10.3390/en13153929

Cristian Napole, Oscar Barambones + Show 2 more

Open Access

https://doi.org/10.3390/en13153929

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Journal: Energies	Publication Date: Aug 1, 2020
Citations: 19	License type: CC BY 4.0

Affiliation: Centro de Tecnologías Aeronauticas (Spain)

Abstract

This paper presents a deep analysis of different feed-forward (FF) techniques combined with two different proportional-integral-derivative (PID) control to guide a real piezoelectric actuator (PEA). These devices are well known for a non-linear effect called “hysteresis” which generates an undesirable performance during the device operation. First, the PEA was analysed under real experiments to determine the response with different frequencies and voltages. Secondly, a voltage and frequency inputs were chosen and a study of different control approaches was performed using a conventional PID in close-loop, adding a linear compensation and a FF with the same PID and an artificial neural network (ANN). Finally, the best result was contrasted with an adaptive PID which used a single neuron (SNPID) combined with Hebbs rule to update its parameters. Results were analysed in terms of guidance, error and control signal whereas the performance was evaluated with the integral of the absolute error (IAE). Experiments showed that the FF-ANN compensation combined with an SNPID was the most efficient.

Highlights

Piezoelectric actuators (PEAs) are positioning systems which have been widely used in the field of micro- and nano-positioning due to their high displacement resolution, large actuation force, high speed response and vast stiffness
Even though the hysteresis is an effect that cannot be excluded, a control strategy should be designed and implemented so that the position error can be diminished and the PEA can be used in a high precision application
Since the displacement measurement device is a strain gauge made of resistances configured as a Wheatstone bridge, certain issues had appeared at the moment of the measurement and it was concluded that the environment temperature had an impact on it

Summary

Introduction

Piezoelectric actuators (PEAs) are positioning systems which have been widely used in the field of micro- and nano-positioning due to their high displacement resolution (around the micrometer), large actuation force (typically several hundred of Newtons), high speed response and vast stiffness. They had been employed in applications such as scanning probe microscopes (SPM), computer components, micro-manipulators, machine tools and energy recovery [1,2]. Even though the hysteresis is an effect that cannot be excluded, a control strategy should be designed and implemented so that the position error can be diminished and the PEA can be used in a high precision application.

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Results

Conclusion