Intelligent Rate-Dependent Hysteresis Control Compensator Design With Bouc-Wen Model Based on RMSO for Piezoelectric Actuator

Dongbo Liu,Haibin Wang,Yu Fang

doi:10.1109/access.2020.2984645

Dongbo Liu, Haibin Wang + Show 1 more

Open Access

https://doi.org/10.1109/access.2020.2984645

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Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 34	License type: CC BY 4.0

Affiliation: Xihua University, Yamaguchi University

Abstract

Piezoelectric actuators (PAs) require high precision positioning for the applications of micro electrical mechanical systems, but it exhibits hysteresis nonlinearity which deteriorates positioning accuracy if no proper compensation is given. Hysteresis nonlinear modeling of PAs is a prime choice for hysteresis compensation. This paper proposes a novel intelligent positioning control algorithm based on Bouc-Wen (BW) model for the compensation of a bi-morph type piezoelectric actuator (PA) suffering rate-dependent hysteresis. A region based mixed-species swarm optimization (RMSO) algorithm is proposed for BW modeling to capture the dynamic nonlinearity of a piezoelectric actuator which exhibits rate-dependent hysteresis. Results of numerical simulations have been disclosed to illustrate the performance enhancement of RMSO over classical algorithm while they are applied to the parameter fitting problem of BW model for experimentally acquired datasets. An model based adaptive Fuzzy neural network (Fuzzy-NN) controller of PA is utilized to compensate the hysteresis for the positioning tracking control. Experimental results also illustrate the good performance of the proposed RMSO-BW based control scheme for the hysteresis compensation control of the PA.

Highlights

Smart materials are widely used in industries and appliances as parts of smart systems
This paper proposes a region based mixed-species swarm optimization which is hereafter abbreviated as RMSO for parameter determination of BW model
The results shown the BW modeling can capture the characteristic of hysteresis of Piezoelectric actuators (PAs), the accuracy of BW modeling based on RMSO better results than the one obtained with genetic algorithm (GA) in this specific condition

Summary

INTRODUCTION

Smart materials are widely used in industries and appliances as parts of smart systems. In order to improve the BW modeling for the hysteresis compensation in micro electro mechanical systems, a region based mixed-species swarm optimization which investigates swarm intelligent computing abstracted from the diversified ecology structure of environment is proposed for the parameters optimization of BW modeling. D. Liu et al.: Intelligent Rate-Dependent Hysteresis Control Compensator Design With Bouc-Wen Model Based on RMSO for PA. The hysteretic nonlinearity leads to positioning errors which significantly hinder the operating speed and precision, the aim of this research to apply BW model to capture the hysteresis behavior of systems well. The four parameters (α, β, γ and n) of the BW hysteretic model need to be adjusted appropriately With this aim in mind, we proposed a new method which will be used throughout this paper, and the details and process of BW hsyteretic modeling will be introduced

EXPERIMENTAL APPARATUS AND SETUP

EXPERIMENTAL RESULTS AND ANALYSIS

CONCLUSION