Distributed fixed-time formation tracking control for multiple underactuated USVs with lumped uncertainties and input saturation

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS ISA transactions Pub Date : 2024-11-01 DOI:10.1016/j.isatra.2024.08.022
Junpeng Li, Yunsheng Fan, Jiaxian Liu
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Abstract

A fixed-time distributed formation control strategy is investigated for multiple underactuated unmanned surface vehicles (USVs) with unmeasured velocities and input saturation. Initially, a necessary coordinate transformation is applied to the mathematical model of USVs to address the underactuated issue. Subsequently, a fixed-time extended state observer (FESO) is constructed to estimate unmeasured velocities and lumped disturbances of USVs based on input and output data in the control loop. Meanwhile, the leader–follower approach is applied to achieve a preset formation. A fixed-time differentiator is utilized to compute real-time differential signals for virtual control laws, which simplifies the complexity of controller design. Furthermore, a fixed-time distributed formation controller is designed based on an asymmetric differentiable saturation model. The effects of input saturation are eliminated by a designed auxiliary system. Finally, the fixed-time stability of the closed-loop system is analyzed through the Lyapunov stability theory. The comparison simulation results verify the effectiveness and superiority of the proposed formation control scheme.
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具有叠加不确定性和输入饱和度的多艘欠驱动 USV 的分布式固定时间编队跟踪控制。
本文研究了一种固定时间分布式编队控制策略,适用于速度无法测量且输入饱和的多个未充分驱动的无人水面飞行器(USV)。首先,对 USV 的数学模型进行必要的坐标变换,以解决驱动不足的问题。随后,构建一个固定时间扩展状态观测器(FESO),以根据控制环路中的输入和输出数据估计 USV 的未测量速度和叠加干扰。同时,采用领导者-跟随者方法实现预设编队。利用固定时间微分器计算虚拟控制法则的实时微分信号,从而简化了控制器设计的复杂性。此外,还根据非对称可微分饱和模型设计了固定时间分布式编队控制器。设计的辅助系统消除了输入饱和的影响。最后,通过 Lyapunov 稳定性理论分析了闭环系统的固定时间稳定性。对比仿真结果验证了所提编队控制方案的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
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.
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