{"title":"基于改进递推最小二乘算法的传感器动态补偿","authors":"Yijiang Liu, Shuanghong Liu, Zhenzhen Qin, Zhijie Zhang, Lifan Meng","doi":"10.1109/ICMA.2013.6617917","DOIUrl":null,"url":null,"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.","PeriodicalId":335884,"journal":{"name":"2013 IEEE International Conference on Mechatronics and Automation","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Dynamic compensation of sensors based on improved recursive least squares algorithm\",\"authors\":\"Yijiang Liu, Shuanghong Liu, Zhenzhen Qin, Zhijie Zhang, Lifan Meng\",\"doi\":\"10.1109/ICMA.2013.6617917\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":335884,\"journal\":{\"name\":\"2013 IEEE International Conference on Mechatronics and Automation\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Mechatronics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMA.2013.6617917\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Mechatronics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2013.6617917","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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. 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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