{"title":"基于神经网络的硬盘自传感微驱动器二自由度控制","authors":"M. Sasaki, K. Fujihara, H. Yamada, Y. Nam, S. Ito","doi":"10.1109/ISIC.2007.4450902","DOIUrl":null,"url":null,"abstract":"The present paper describes a two-degree-of-freedom control of a self-sensing micro-actuator for a dual-stage hard disk drive using neural networks. The two-degree-of-freedom control system is comprised of a feedforward controller and a feedback controller. Two neural networks are developed for the two-degree-of-freedom control system, one for the inverse dynamic model for the feedforward controller and one for system identification for the generation of the desired self-sensing signal. The feedback controller can realize the identified self-sensing signal. The micro-actuator uses a PZT actuator pair, installed on the assembly of the suspension. The self-sensing micro-actuator can be used to form a combined actuation and sensing mechanism. Experimental results show that the neural network approach can be used effectively for the control and identification of the self-sensing micro-actuator system","PeriodicalId":415827,"journal":{"name":"2006 9th International Conference on Control, Automation, Robotics and Vision","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Two-Degree-of-Freedom Control of a Self-Sensing Micro-Actuator for HDD using Neural Networks\",\"authors\":\"M. Sasaki, K. Fujihara, H. Yamada, Y. Nam, S. Ito\",\"doi\":\"10.1109/ISIC.2007.4450902\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The present paper describes a two-degree-of-freedom control of a self-sensing micro-actuator for a dual-stage hard disk drive using neural networks. The two-degree-of-freedom control system is comprised of a feedforward controller and a feedback controller. Two neural networks are developed for the two-degree-of-freedom control system, one for the inverse dynamic model for the feedforward controller and one for system identification for the generation of the desired self-sensing signal. The feedback controller can realize the identified self-sensing signal. The micro-actuator uses a PZT actuator pair, installed on the assembly of the suspension. The self-sensing micro-actuator can be used to form a combined actuation and sensing mechanism. Experimental results show that the neural network approach can be used effectively for the control and identification of the self-sensing micro-actuator system\",\"PeriodicalId\":415827,\"journal\":{\"name\":\"2006 9th International Conference on Control, Automation, Robotics and Vision\",\"volume\":\"114 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 9th International Conference on Control, Automation, Robotics and Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIC.2007.4450902\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 9th International Conference on Control, Automation, Robotics and Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIC.2007.4450902","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Two-Degree-of-Freedom Control of a Self-Sensing Micro-Actuator for HDD using Neural Networks
The present paper describes a two-degree-of-freedom control of a self-sensing micro-actuator for a dual-stage hard disk drive using neural networks. The two-degree-of-freedom control system is comprised of a feedforward controller and a feedback controller. Two neural networks are developed for the two-degree-of-freedom control system, one for the inverse dynamic model for the feedforward controller and one for system identification for the generation of the desired self-sensing signal. The feedback controller can realize the identified self-sensing signal. The micro-actuator uses a PZT actuator pair, installed on the assembly of the suspension. The self-sensing micro-actuator can be used to form a combined actuation and sensing mechanism. Experimental results show that the neural network approach can be used effectively for the control and identification of the self-sensing micro-actuator system