Global fixed-time position-constrained guidance and adaptive fuzzy prescribed performance control using novel shift function for multiple unmanned surface vehicles formation
{"title":"Global fixed-time position-constrained guidance and adaptive fuzzy prescribed performance control using novel shift function for multiple unmanned surface vehicles formation","authors":"Haiyan Tong, Mingxiao Sun, Tiantian Luan","doi":"10.1016/j.isatra.2025.02.034","DOIUrl":null,"url":null,"abstract":"<div><div>Guidance and control of multiple unmanned surface vehicles (Multi-USVs) present many challenges due to their under-actuation and the unknown environmental disturbance. This research addresses the formation guidance and control problems of multi-USVs by designing a global fixed-time constrained guidance and control formation approach. First, a global fixed-time control Lyapunov function (GFCLF) is proposed using an innovative shift function to deal with the fixed-time output partial constraint. Subsequently, a fixed-time asymmetric position-constrained guidance algorithm for multi-USVs formation is designed by combining the line-of-sight guidance principle, the leader–follower structure, and the suggested GFCLF. Second, a global fixed-time prescribed performance function (GFPPF) is designed to solve the global tracking error performance constraint problem. Then, global fixed-time adaptive fuzzy prescribed performance control laws are developed to achieve the tracking control for the multi-USVs formation task, in which a fixed-time adaptive fuzzy logic system is designed to approximate the unknown disturbance of USVs. Furthermore, the closed-loop control system stability analysis is proven to support that all tracking error signals are bounded in a fixed time. Finally, simulations and comparative cases using the physical USV model are studied to demonstrate the practicality and superiority of theoretical results.</div></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"160 ","pages":"Pages 58-71"},"PeriodicalIF":6.5000,"publicationDate":"2025-03-08","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/S0019057825001247","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}
引用次数: 0
Abstract
Guidance and control of multiple unmanned surface vehicles (Multi-USVs) present many challenges due to their under-actuation and the unknown environmental disturbance. This research addresses the formation guidance and control problems of multi-USVs by designing a global fixed-time constrained guidance and control formation approach. First, a global fixed-time control Lyapunov function (GFCLF) is proposed using an innovative shift function to deal with the fixed-time output partial constraint. Subsequently, a fixed-time asymmetric position-constrained guidance algorithm for multi-USVs formation is designed by combining the line-of-sight guidance principle, the leader–follower structure, and the suggested GFCLF. Second, a global fixed-time prescribed performance function (GFPPF) is designed to solve the global tracking error performance constraint problem. Then, global fixed-time adaptive fuzzy prescribed performance control laws are developed to achieve the tracking control for the multi-USVs formation task, in which a fixed-time adaptive fuzzy logic system is designed to approximate the unknown disturbance of USVs. Furthermore, the closed-loop control system stability analysis is proven to support that all tracking error signals are bounded in a fixed time. Finally, simulations and comparative cases using the physical USV model are studied to demonstrate the practicality and superiority of theoretical results.
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.