{"title":"未知输入估计量在桥式起重机阻尼振动中的应用","authors":"B. Patartics, B. Kiss","doi":"10.1515/488","DOIUrl":null,"url":null,"abstract":"This paper focuses on the development of state estimation methods for mechanical systems with uncertain frictional parameters. The goal of the study is to provide reliable angle estimation for state-feedback-based crane control solutions, designed to reduce load sway. Cranes are underactuated systems, usually unequipped with the sensors necessary to measure the swinging angle, therefore the damping of their oscillatory behaviour is a challenging task. Two estimators are proposed for the calculation of the unmeasured states. One is based on an ’unknown input Kalman filter’ (UIKF), the other applies the ’unscented Kalman filter’ (UKF) with load prediction. Simulation results are provided to demonstrate the accuracy of the algorithms.","PeriodicalId":13010,"journal":{"name":"Hungarian Journal of Industrial Chemistry","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"The Application of Unknown Input Estimators to Damp Load Oscillations of Overhead Cranes\",\"authors\":\"B. Patartics, B. Kiss\",\"doi\":\"10.1515/488\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper focuses on the development of state estimation methods for mechanical systems with uncertain frictional parameters. The goal of the study is to provide reliable angle estimation for state-feedback-based crane control solutions, designed to reduce load sway. Cranes are underactuated systems, usually unequipped with the sensors necessary to measure the swinging angle, therefore the damping of their oscillatory behaviour is a challenging task. Two estimators are proposed for the calculation of the unmeasured states. One is based on an ’unknown input Kalman filter’ (UIKF), the other applies the ’unscented Kalman filter’ (UKF) with load prediction. Simulation results are provided to demonstrate the accuracy of the algorithms.\",\"PeriodicalId\":13010,\"journal\":{\"name\":\"Hungarian Journal of Industrial Chemistry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hungarian Journal of Industrial Chemistry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/488\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hungarian Journal of Industrial Chemistry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/488","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Application of Unknown Input Estimators to Damp Load Oscillations of Overhead Cranes
This paper focuses on the development of state estimation methods for mechanical systems with uncertain frictional parameters. The goal of the study is to provide reliable angle estimation for state-feedback-based crane control solutions, designed to reduce load sway. Cranes are underactuated systems, usually unequipped with the sensors necessary to measure the swinging angle, therefore the damping of their oscillatory behaviour is a challenging task. Two estimators are proposed for the calculation of the unmeasured states. One is based on an ’unknown input Kalman filter’ (UIKF), the other applies the ’unscented Kalman filter’ (UKF) with load prediction. Simulation results are provided to demonstrate the accuracy of the algorithms.