{"title":"Fixed-Time Optimal Fault-Tolerant Formation Control With Prescribed Performance for Fixed-Wing UAVs Under Dual Faults","authors":"Bo Meng;Ke Zhang;Bin Jiang","doi":"10.1109/TSIPN.2023.3341406","DOIUrl":null,"url":null,"abstract":"This article aims to propose a novel fixed-time distributed optimized formation control scheme for fixed-wing unmanned aerial vehicles with uncertainties, communication link and actuator faults, and performance constraint. Firstly, the prescribed performance function is introduced to improve the steady-state and transient performances of fixed-wing UAVs system. Communication link faults are tolerated by utilizing the distributed leader state observer. Subsequently, with the objective of establishing optimal controllers for velocity and altitude subsystems, the reinforcement learning control method is employed. Simultaneously, an intermediate controller is constructed to tackle the difficulties in applying reinforcement learning to the fault-tolerant control scheme. In addition, new adaptive laws of fault factor parameters are proposed, which can make the fault-tolerant scheme align better with the concept of fixed-time convergence. Finally, fixed-time prescribed performance controllers for velocity and altitude subsystems are developed. The designed control algorithm can ensure that the velocity and altitude tracking errors converge to the prescribed region, and the simulation results further demonstrate that the proposed control strategy is effective.","PeriodicalId":56268,"journal":{"name":"IEEE Transactions on Signal and Information Processing over Networks","volume":"9 ","pages":"875-887"},"PeriodicalIF":3.0000,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Signal and Information Processing over Networks","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10356736/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
This article aims to propose a novel fixed-time distributed optimized formation control scheme for fixed-wing unmanned aerial vehicles with uncertainties, communication link and actuator faults, and performance constraint. Firstly, the prescribed performance function is introduced to improve the steady-state and transient performances of fixed-wing UAVs system. Communication link faults are tolerated by utilizing the distributed leader state observer. Subsequently, with the objective of establishing optimal controllers for velocity and altitude subsystems, the reinforcement learning control method is employed. Simultaneously, an intermediate controller is constructed to tackle the difficulties in applying reinforcement learning to the fault-tolerant control scheme. In addition, new adaptive laws of fault factor parameters are proposed, which can make the fault-tolerant scheme align better with the concept of fixed-time convergence. Finally, fixed-time prescribed performance controllers for velocity and altitude subsystems are developed. The designed control algorithm can ensure that the velocity and altitude tracking errors converge to the prescribed region, and the simulation results further demonstrate that the proposed control strategy is effective.
期刊介绍:
The IEEE Transactions on Signal and Information Processing over Networks publishes high-quality papers that extend the classical notions of processing of signals defined over vector spaces (e.g. time and space) to processing of signals and information (data) defined over networks, potentially dynamically varying. In signal processing over networks, the topology of the network may define structural relationships in the data, or may constrain processing of the data. Topics include distributed algorithms for filtering, detection, estimation, adaptation and learning, model selection, data fusion, and diffusion or evolution of information over such networks, and applications of distributed signal processing.