{"title":"双级硬盘驱动器闭环微驱动器行程干扰建模与预测","authors":"Manas Chakraborty, R. Caverly","doi":"10.1115/1.4056025","DOIUrl":null,"url":null,"abstract":"\n This letter presents a method to model the disturbance environment of a dual-stage hard disk drive (HDD), which is then used to predict the actuator stroke usage (i.e., the range of actuator displacement used) of a closed-loop track-following controller. In particular, a data driven disturbance modeling approach is proposed and the stochastic interpretation of the H2 norm is used to systematically estimate the microactuator (PZT) stroke usage of the HDD controller. Upper and lower-bound models of the frequency response of the external disturbance environment are used to provide a range of possible stroke usage, which involves a data-driven calibration process. The accuracy of the prediction model is validated in experiments with a controller that differs from the controllers in the calibration data set.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":"173 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Disturbance Modeling and Prediction of Closed-Loop Micro-Actuator Stroke Usage in Dual-Stage Hard Disk Drives\",\"authors\":\"Manas Chakraborty, R. Caverly\",\"doi\":\"10.1115/1.4056025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n This letter presents a method to model the disturbance environment of a dual-stage hard disk drive (HDD), which is then used to predict the actuator stroke usage (i.e., the range of actuator displacement used) of a closed-loop track-following controller. In particular, a data driven disturbance modeling approach is proposed and the stochastic interpretation of the H2 norm is used to systematically estimate the microactuator (PZT) stroke usage of the HDD controller. Upper and lower-bound models of the frequency response of the external disturbance environment are used to provide a range of possible stroke usage, which involves a data-driven calibration process. The accuracy of the prediction model is validated in experiments with a controller that differs from the controllers in the calibration data set.\",\"PeriodicalId\":327130,\"journal\":{\"name\":\"ASME Letters in Dynamic Systems and Control\",\"volume\":\"173 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ASME Letters in Dynamic Systems and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4056025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ASME Letters in Dynamic Systems and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4056025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Disturbance Modeling and Prediction of Closed-Loop Micro-Actuator Stroke Usage in Dual-Stage Hard Disk Drives
This letter presents a method to model the disturbance environment of a dual-stage hard disk drive (HDD), which is then used to predict the actuator stroke usage (i.e., the range of actuator displacement used) of a closed-loop track-following controller. In particular, a data driven disturbance modeling approach is proposed and the stochastic interpretation of the H2 norm is used to systematically estimate the microactuator (PZT) stroke usage of the HDD controller. Upper and lower-bound models of the frequency response of the external disturbance environment are used to provide a range of possible stroke usage, which involves a data-driven calibration process. The accuracy of the prediction model is validated in experiments with a controller that differs from the controllers in the calibration data set.