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Hysteresis Characteristics Study Of PZT In Heterodyne Interferometric Nano-positioning System

Posted on:2016-08-04Degree:MasterType:Thesis
Country:ChinaCandidate:F QianFull Text:PDF
GTID:2272330470969590Subject:Detection Technology and Automation
Abstract/Summary:PDF Full Text Request
With the further development in high-precision machining and other high-tech industry, their requirement for running and positioning accuracy is becoming more sophisticated, so the research of micro-positioners is supported by more and more attention.Due to its high displacement resolution and big clamping force, piezoelectric drivers are widely used in various high-precision positioning fields. However,piezoelectric actuators also have inherent hysteresis and creep nonlinear characteristics, thus the accuracy of positioning system will be reduced. Since the hysteresis nonlinear phenomenon of piezoelectric ceramic is the major factor affecting the accuracy of the micro/nano-positioning system. Therefore, in order to obtain the high positioning accuracy and ideal dynamic response, we should study the hysteresis nonlinear characteristics of piezoelectric actuators, construct the hysteresis mathematical model of piezoelectric actuators, and then design the corresponding controllers.This paper introduces the composition of micro/nano-measurement system, and analyzes the reasons of hysteresis nonlinear of the piezoelectric ceramic actuators of stack type. Based on the micro/nano-measurement system, isolation function of the system is tested to verify the good performance of the isolation platform. Under these experimental conditions, hysteresis phenomenon of piezoelectric actuators is measured experimentally, then we analyze the rules and characteristics of hysteresis.This paper proposes a neural network modeling method based on polynomial fitting algorithm, so the BP neural network model of hysteresis of the piezoelectric ceramic drivers is set up by using the tested data. Based on the hysteresis model, we use the feed-forward method, the feed-forward combined with PID method and single neuron self-adaptive PID to control the displacement of piezoelectric actuators respectively, then hysteresis characteristics in piezoelectric ceramic drivers is compensated, and the impact of hysteresis nonlinear in system is reduced, thus thepositioning accuracy of micro/nano-positioning system is improved.
Keywords/Search Tags:piezoelectric ceramic actuators, hysteresis phenomenon, polynomial fitting, neural network modeling, nano-positioning
PDF Full Text Request
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