{"title":"Predictive control of linear time-varying model for hydraulic erecting systems based on linear expanded state observer","authors":"Dong Ma, Zhihao Liu, Qinhe Gao, Lei Gao","doi":"10.1177/16878132241266757","DOIUrl":null,"url":null,"abstract":"By analyzing the deficiencies of existing hydraulic erecting systems (HESs) control methods, this study proposes a linear time-varying model predictive control (LTV-MPC) method based on the linear extended state observer (LESO) for HESs. First, the working mechanism of HESs is methodically analyzed and the corresponding state space equations are established. Second, the LESO system is designed to estimate the current unknown real-time states. Then, the LTV-MPC is employed to evaluate and output the optimal solution of the servo voltage signal. Finally, through simulation and experiment, the effectiveness of the proposed method is confirmed and discussed. The results show that the displacement error rate of the proposed method is still lower than 0.223% under larger external disturbances, which can effectively improve the control accuracy and stability of the system compared with other methods.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Mechanical Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/16878132241266757","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
By analyzing the deficiencies of existing hydraulic erecting systems (HESs) control methods, this study proposes a linear time-varying model predictive control (LTV-MPC) method based on the linear extended state observer (LESO) for HESs. First, the working mechanism of HESs is methodically analyzed and the corresponding state space equations are established. Second, the LESO system is designed to estimate the current unknown real-time states. Then, the LTV-MPC is employed to evaluate and output the optimal solution of the servo voltage signal. Finally, through simulation and experiment, the effectiveness of the proposed method is confirmed and discussed. The results show that the displacement error rate of the proposed method is still lower than 0.223% under larger external disturbances, which can effectively improve the control accuracy and stability of the system compared with other methods.
期刊介绍:
Advances in Mechanical Engineering (AIME) is a JCR Ranked, peer-reviewed, open access journal which publishes a wide range of original research and review articles. The journal Editorial Board welcomes manuscripts in both fundamental and applied research areas, and encourages submissions which contribute novel and innovative insights to the field of mechanical engineering