{"title":"Predefined-Time Stabilization for Low-Order Nonlinear Systems With Time-Varying Orders and Output Constraint","authors":"Gang Sun, Rong-Heng Cui","doi":"10.1002/rnc.7733","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>This paper solves the problem of predefined-time stabilization for low-order nonlinear systems with time-varying orders and the asymmetric output constraint. We construct a tangent-type barrier Lyapunov function to handle the output constraint. By using the presented barrier Lyapunov function and the adding a power integrator technique, a novel continuous state-feedback controller is designed to guarantee that the solution of the closed-loop system is predefined-time stable while the output constraint is not transgressed.</p>\n </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 4","pages":"1473-1485"},"PeriodicalIF":3.2000,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Robust and Nonlinear Control","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/rnc.7733","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper solves the problem of predefined-time stabilization for low-order nonlinear systems with time-varying orders and the asymmetric output constraint. We construct a tangent-type barrier Lyapunov function to handle the output constraint. By using the presented barrier Lyapunov function and the adding a power integrator technique, a novel continuous state-feedback controller is designed to guarantee that the solution of the closed-loop system is predefined-time stable while the output constraint is not transgressed.
期刊介绍：
Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
