Dynamic compensation of sensors based on improved recursive least squares algorithm

In order to eliminate the sensor's dynamic error, a method that improved recursive least squares method is proposed. Gradient descent method is used to generate the initial value of the filter parameters, then the recursive least squares method (RLS) algorithm is used to optimize the parameters...

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Bibliographic Details
Published in2013 IEEE International Conference on Mechatronics and Automation pp. 196 - 200
Main Authors Yijiang Liu, Shuanghong Liu, Zhenzhen Qin, Zhijie Zhang, Lifan Meng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2013
Subjects
Aerodynamics
dynamic characteristic
dynamic compensation
Heuristic algorithms
improved RLS algorithm
Mathematical model
matlab
sensor
Sensor phenomena and characterization
Sensor systems
Time-domain analysis
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ISBN1467355577
9781467355575
ISSN2152-7431
DOI10.1109/ICMA.2013.6617917

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Summary:In order to eliminate the sensor's dynamic error, a method that improved recursive least squares method is proposed. Gradient descent method is used to generate the initial value of the filter parameters, then the recursive least squares method (RLS) algorithm is used to optimize the parameters. The algorithm is tested and verified on the matlab platform. The time-domain response and frequency domain response of the sensor are analyzed before and after compensation. The piezoelectric sensor CY_YD-205 is compensated. Engineering experiments show that the compensation filter designed by the improved recursive least squares algorithm can improve the dynamic characteristics of the sensor system.
ISBN:1467355577
9781467355575
ISSN:2152-7431
DOI:10.1109/ICMA.2013.6617917