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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| Published in | 2013 IEEE International Conference on Mechatronics and Automation pp. 196 - 200 |
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| Main Authors | , , , , |
| Format | Conference Proceeding |
| Language | English |
| Published |
IEEE
01.08.2013
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| Subjects | |
| Online Access | Get full text |
| ISBN | 1467355577 9781467355575 |
| ISSN | 2152-7431 |
| DOI | 10.1109/ICMA.2013.6617917 |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Zhenzhen Qin Shuanghong Liu Lifan Meng Yijiang Liu Zhijie Zhang |
| Author_xml | – sequence: 1 surname: Yijiang Liu fullname: Yijiang Liu organization: Meas. Lab., North Univ. of China, Taiyuan, China – sequence: 2 surname: Shuanghong Liu fullname: Shuanghong Liu organization: Meas. Lab., North Univ. of China, Taiyuan, China – sequence: 3 surname: Zhenzhen Qin fullname: Zhenzhen Qin organization: Meas. Lab., North Univ. of China, Taiyuan, China – sequence: 4 surname: Zhijie Zhang fullname: Zhijie Zhang email: yi9jiang@163.com organization: Meas. Lab., North Univ. of China, Taiyuan, China – sequence: 5 surname: Lifan Meng fullname: Lifan Meng organization: Meas. Lab., North Univ. of China, Taiyuan, China |
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| Snippet | 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... |
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| SubjectTerms | Aerodynamics dynamic characteristic dynamic compensation Heuristic algorithms improved RLS algorithm Mathematical model matlab sensor Sensor phenomena and characterization Sensor systems Time-domain analysis |
| Title | Dynamic compensation of sensors based on improved recursive least squares algorithm |
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