{"title":"Fast Finite-Time Bipartite Formation With Obstacle Avoidance for Time-Delay Multiagent Systems: Application in Mobile Robot Swarm","authors":"Zhenyu Chang;Guangdeng Zong;Shiji Song;Xudong Zhao","doi":"10.1109/TII.2025.3545050","DOIUrl":null,"url":null,"abstract":"The bipartite formation allows agents to achieve two formation structures in opposite directions and finds wide applications in social as well as natural situations. This article investigates the fast finite-time bipartite formation control problem for time-delay nonlinear multiagent systems operating in an obstacle environment. A fuzzy adaptive formation control strategy is proposed utilizing the leader-following method, under which the desired formation is achieved at a fast convergence rate. Since the practical actuator output is usually limited and susceptible to faults, its antisaturation and fault-tolerance capacities are thus considered in the controller construction. Moreover, an obstacle avoidance mechanism is embedded in the control strategy utilizing the artificial potential field method, ensuring the security operation of the formation. An improved Lyapunov–Krasovskii functional is constructed for the stability analysis, which makes full use of the time-delay information of the system. The fast finite-time convergence of the formation error system and the feasibility of obstacle avoidance behavior are verified with the Lyapunov stability theory and the designed energy function. Finally, the proposed control strategy is applied to the bipartite formation control task of a mobile robot swarm, and sufficient simulation results are presented to demonstrate the effectiveness of the theoretical analysis.","PeriodicalId":13301,"journal":{"name":"IEEE Transactions on Industrial Informatics","volume":"21 6","pages":"4586-4594"},"PeriodicalIF":9.9000,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Informatics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10918888/","RegionNum":1,"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}
引用次数: 0
Abstract
The bipartite formation allows agents to achieve two formation structures in opposite directions and finds wide applications in social as well as natural situations. This article investigates the fast finite-time bipartite formation control problem for time-delay nonlinear multiagent systems operating in an obstacle environment. A fuzzy adaptive formation control strategy is proposed utilizing the leader-following method, under which the desired formation is achieved at a fast convergence rate. Since the practical actuator output is usually limited and susceptible to faults, its antisaturation and fault-tolerance capacities are thus considered in the controller construction. Moreover, an obstacle avoidance mechanism is embedded in the control strategy utilizing the artificial potential field method, ensuring the security operation of the formation. An improved Lyapunov–Krasovskii functional is constructed for the stability analysis, which makes full use of the time-delay information of the system. The fast finite-time convergence of the formation error system and the feasibility of obstacle avoidance behavior are verified with the Lyapunov stability theory and the designed energy function. Finally, the proposed control strategy is applied to the bipartite formation control task of a mobile robot swarm, and sufficient simulation results are presented to demonstrate the effectiveness of the theoretical analysis.
期刊介绍:
The IEEE Transactions on Industrial Informatics is a multidisciplinary journal dedicated to publishing technical papers that connect theory with practical applications of informatics in industrial settings. It focuses on the utilization of information in intelligent, distributed, and agile industrial automation and control systems. The scope includes topics such as knowledge-based and AI-enhanced automation, intelligent computer control systems, flexible and collaborative manufacturing, industrial informatics in software-defined vehicles and robotics, computer vision, industrial cyber-physical and industrial IoT systems, real-time and networked embedded systems, security in industrial processes, industrial communications, systems interoperability, and human-machine interaction.