{"title":"严格反馈非线性先导系统的分布扩展状态观测器设计。","authors":"Jixing Lv , Changhong Wang , Yonggui Kao","doi":"10.1016/j.isatra.2025.05.015","DOIUrl":null,"url":null,"abstract":"<div><div>Knowing the leader’s state and dynamics is crucial for leader-following control. This article addresses the distributed state/uncertainty estimation problem for a strict-feedback nonlinear leader system under directed communication topologies. The leader is characterized by Hölder-growing nonlinearities and matched uncertainty. A prescribed-time distributed estimation scheme composed of two distributed extended state observers (DESOs) is proposed. Each follower (observer node) receives only one-dimensional output estimates from its neighbors and at most one-dimensional output from the leader system, effectively reducing the communication load. First, a prescribed-time DESO (PTDESO) is proposed so that each follower can reconstruct the leader’s state and uncertainty at a time tightly prescribed by a single parameter, uniform to the initial conditions. Then, a high-gain DESO (HGDESO) is constructed, which achieves asymptotic convergence and maintains the observation errors in a small neighborhood of the origin after the prescribed time. Sufficient conditions for guaranteeing the convergence of the two DESOs are established. Ultimately, practical examples involving multiple manipulators and marine surface vehicles are provided to demonstrate the effectiveness of the proposed observers.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"163 ","pages":"Pages 120-130"},"PeriodicalIF":6.3000,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Distributed extended state observer design for strict-feedback nonlinear leader system\",\"authors\":\"Jixing Lv , Changhong Wang , Yonggui Kao\",\"doi\":\"10.1016/j.isatra.2025.05.015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Knowing the leader’s state and dynamics is crucial for leader-following control. This article addresses the distributed state/uncertainty estimation problem for a strict-feedback nonlinear leader system under directed communication topologies. The leader is characterized by Hölder-growing nonlinearities and matched uncertainty. A prescribed-time distributed estimation scheme composed of two distributed extended state observers (DESOs) is proposed. Each follower (observer node) receives only one-dimensional output estimates from its neighbors and at most one-dimensional output from the leader system, effectively reducing the communication load. First, a prescribed-time DESO (PTDESO) is proposed so that each follower can reconstruct the leader’s state and uncertainty at a time tightly prescribed by a single parameter, uniform to the initial conditions. Then, a high-gain DESO (HGDESO) is constructed, which achieves asymptotic convergence and maintains the observation errors in a small neighborhood of the origin after the prescribed time. Sufficient conditions for guaranteeing the convergence of the two DESOs are established. Ultimately, practical examples involving multiple manipulators and marine surface vehicles are provided to demonstrate the effectiveness of the proposed observers.</div></div>\",\"PeriodicalId\":14660,\"journal\":{\"name\":\"ISA transactions\",\"volume\":\"163 \",\"pages\":\"Pages 120-130\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISA transactions\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0019057825002496\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISA transactions","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0019057825002496","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Distributed extended state observer design for strict-feedback nonlinear leader system
Knowing the leader’s state and dynamics is crucial for leader-following control. This article addresses the distributed state/uncertainty estimation problem for a strict-feedback nonlinear leader system under directed communication topologies. The leader is characterized by Hölder-growing nonlinearities and matched uncertainty. A prescribed-time distributed estimation scheme composed of two distributed extended state observers (DESOs) is proposed. Each follower (observer node) receives only one-dimensional output estimates from its neighbors and at most one-dimensional output from the leader system, effectively reducing the communication load. First, a prescribed-time DESO (PTDESO) is proposed so that each follower can reconstruct the leader’s state and uncertainty at a time tightly prescribed by a single parameter, uniform to the initial conditions. Then, a high-gain DESO (HGDESO) is constructed, which achieves asymptotic convergence and maintains the observation errors in a small neighborhood of the origin after the prescribed time. Sufficient conditions for guaranteeing the convergence of the two DESOs are established. Ultimately, practical examples involving multiple manipulators and marine surface vehicles are provided to demonstrate the effectiveness of the proposed observers.
期刊介绍:
ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.