Robust predefined fixed-time formation-containment control for multiple unmanned surface vehicles with input saturation

IF 6.5 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Yong Chen , Jinlong Huang , Fuxi Niu , Xunhua Dai , Haoyue Huang
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引用次数: 0

Abstract

The predefined fixed-time formation-containment (PFTFC) control problem for unmanned surface vehicles (USVs) under unknown disturbances and input saturation is investigated, where the leaders form a formation configuration and the followers converge to the predefined convex hull formed by the leaders within a fixed time. To address this issue, a two-layer framework is introduced, decomposing the problem into trajectory estimation and trajectory tracking components. In the first layer, a novel fixed-time trajectory estimator is proposed for the leaders and the followers to estimate the desired trajectory. In the second layer, to eliminate the effects of unknown disturbances and input saturation, a fixed-time disturbance observer and an auxiliary system are proposed. Then combining fixed-time Lyapunov stability and integral sliding mode control, fixed-time control laws are proposed for both the leaders and the followers, respectively. Finally, a numerical simulation example is presented to illustrate the effectiveness of the method introduced in this paper.
具有输入饱和的多无人水面车辆鲁棒预定义固定时间地层遏制控制。
研究了未知干扰和输入饱和条件下无人水面飞行器(usv)的预定义定时队形约束控制问题,其中领队形成队形,随从在固定时间内收敛于由领队形成的预定义凸包。为了解决这一问题,引入了一个两层框架,将问题分解为轨迹估计和轨迹跟踪两个部分。在第一层,提出了一种新的固定时间轨迹估计器,用于领导者和追随者估计期望的轨迹。在第二层,为了消除未知干扰和输入饱和的影响,提出了定时干扰观测器和辅助系统。然后结合定时Lyapunov稳定性和积分滑模控制,分别提出了领导者和追随者的定时控制律。最后,通过数值仿真实例验证了本文方法的有效性。
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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