Adaptive Fuzzy Bipartite Time-Varying Formation Tracking Control for Multiple Lagrangian Systems With Lumped Uncertainties via Finite-Time Hierarchical Mechanism

IF 3.9 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-12-02 DOI:10.1002/acs.3944

Shuang Wang, Tao Han, Bo Xiao, Huaicheng Yan

{"title":"Adaptive Fuzzy Bipartite Time-Varying Formation Tracking Control for Multiple Lagrangian Systems With Lumped Uncertainties via Finite-Time Hierarchical Mechanism","authors":"Shuang Wang, Tao Han, Bo Xiao, Huaicheng Yan","doi":"10.1002/acs.3944","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>This article explores the bipartite time-varying formation tracking problem for multiple Lagrangian systems in the presence of lumped uncertainties, including friction, external disturbances, and actuator faults. To tackle this challenging problem, a finite-time hierarchical mechanism is designed without prior knowledge of uncertainties, which decomposes the above issue into two sub-control problems: 1) the distributed finite-time estimation problem and 2) the local adaptive fuzzy tracking problem. The distributed estimator algorithm is developed to achieve a finite-time bipartite time-varying formation configuration under a cooperative-antagonistic interaction topology. Further, these estimated states are employed to construct the adaptive fuzzy tracking controller based on fuzzy-logic systems and fault-tolerant techniques. Lyapunov functions are utilized to ensure that the considered systems attain the desired formation while maintaining finite-time stability of tracking errors. Finally, simulation experiments are performed to verify the effectiveness of the proposed control algorithm.</p>\n </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 2","pages":"383-397"},"PeriodicalIF":3.9000,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Adaptive Control and Signal Processing","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/acs.3944","RegionNum":4,"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 article explores the bipartite time-varying formation tracking problem for multiple Lagrangian systems in the presence of lumped uncertainties, including friction, external disturbances, and actuator faults. To tackle this challenging problem, a finite-time hierarchical mechanism is designed without prior knowledge of uncertainties, which decomposes the above issue into two sub-control problems: 1) the distributed finite-time estimation problem and 2) the local adaptive fuzzy tracking problem. The distributed estimator algorithm is developed to achieve a finite-time bipartite time-varying formation configuration under a cooperative-antagonistic interaction topology. Further, these estimated states are employed to construct the adaptive fuzzy tracking controller based on fuzzy-logic systems and fault-tolerant techniques. Lyapunov functions are utilized to ensure that the considered systems attain the desired formation while maintaining finite-time stability of tracking errors. Finally, simulation experiments are performed to verify the effectiveness of the proposed control algorithm.

Abstract Image

查看原文本刊更多论文

求助全文

约1分钟内获得全文求助全文

来源期刊

International Journal of Adaptive Control and Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

16.10%

发文量

163

审稿时长

5 months

期刊介绍： The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.