{"title":"Human-in-the-Loop Coordinated Path Following of Marine Vehicles Based on Continuous Twisting Control","authors":"Mingao Lv;Nan Gu;Dan Wang;Bing Han;Zhouhua Peng","doi":"10.1109/TII.2024.3452760","DOIUrl":null,"url":null,"abstract":"This article addresses the coordinated path-following (CPF) control under human supervision for marine vehicles (MVs) with unknown disturbances. A human-in-the-loop coordinated path-following (HCPF) control architecture is proposed based on the robust exact differentiator (RED) observer and the output feedback continuous twisting control (OFCTC) method. Specifically, a human manipulation is introduced into a virtual leader to regulate its path update speed in response to sudden circumstances for the follower MVs. All follower MVs synchronize indirectly with the human-in-the-loop virtual leader over a communication graph. Then, the path-following control problem is transformed into the controls of a second-order along-track error dynamic and a third-order cross-track error dynamic. By using the path-following errors only, the RED observers are developed to recover the unknown states of the error dynamics. Finally, the OFCTC laws are designed to achieve the individual path following in finite time regardless of the lumped disturbances. The stability of the closed-loop system is analyzed by employing the cascade theory. A salient feature of the proposed HCPF control architecture is that the CPF for MVs can be implemented under the supervision and intervention of human. Simulation results are given to illustrate the effectiveness of the proposed HCPF control method.","PeriodicalId":13301,"journal":{"name":"IEEE Transactions on Industrial Informatics","volume":"21 1","pages":"465-474"},"PeriodicalIF":9.9000,"publicationDate":"2024-09-18","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/10683954/","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
This article addresses the coordinated path-following (CPF) control under human supervision for marine vehicles (MVs) with unknown disturbances. A human-in-the-loop coordinated path-following (HCPF) control architecture is proposed based on the robust exact differentiator (RED) observer and the output feedback continuous twisting control (OFCTC) method. Specifically, a human manipulation is introduced into a virtual leader to regulate its path update speed in response to sudden circumstances for the follower MVs. All follower MVs synchronize indirectly with the human-in-the-loop virtual leader over a communication graph. Then, the path-following control problem is transformed into the controls of a second-order along-track error dynamic and a third-order cross-track error dynamic. By using the path-following errors only, the RED observers are developed to recover the unknown states of the error dynamics. Finally, the OFCTC laws are designed to achieve the individual path following in finite time regardless of the lumped disturbances. The stability of the closed-loop system is analyzed by employing the cascade theory. A salient feature of the proposed HCPF control architecture is that the CPF for MVs can be implemented under the supervision and intervention of human. Simulation results are given to illustrate the effectiveness of the proposed HCPF control method.
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.