Adaptive fixed-time stabilization for high-order uncertain nonlinear systems with unknown measurement sensitivities

IF 3.7 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2024-08-28 DOI:10.1016/j.jfranklin.2024.107206
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Abstract

This paper investigates the adaptive fixed-time stabilization problem for a class of uncertain high-order nonlinear systems with unknown measurement sensitivities and unknown control magnitude. Compared to existing practical fixed-time control approaches, our control strategy is capable of driving all states of uncertain high-order systems to the origin within a fixed time, rather than just ensuring their boundedness. Additionally, this study relaxes the restrictions on the nonlinear functions of the system, while overcoming challenges such as unknown control magnitude and unknown measurement sensitivity without prior boundaries. To achieve the control objectives, our control strategy consists of two main steps. Firstly, we divide the initial value of the high-order system into two cases, and construct adaptive controllers separately for each case by adding a power integral technique and backstepping method. Subsequently, the reliance of the stability time of the closed-loop high-order system on the initial value is eliminated by designing an appropriate controller switching mechanism. Finally, we provide a simulation example to validate the effectiveness of our control strategy.

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具有未知测量敏感性的高阶不确定非线性系统的自适应固定时间稳定技术
本文研究了一类具有未知测量敏感性和未知控制量级的不确定高阶非线性系统的自适应固定时间稳定问题。与现有的实用固定时间控制方法相比,我们的控制策略能够在固定时间内将不确定高阶系统的所有状态推向原点,而不仅仅是确保它们的有界性。此外,这项研究还放宽了对系统非线性函数的限制,同时克服了未知控制量级和未知测量灵敏度等挑战,而且没有预先界限。为了实现控制目标,我们的控制策略主要包括两个步骤。首先,我们将高阶系统的初始值分为两种情况,并通过添加功率积分技术和反步进方法,分别为每种情况构建自适应控制器。随后,通过设计适当的控制器切换机制,消除闭环高阶系统的稳定时间对初始值的依赖。最后,我们提供了一个仿真实例来验证我们控制策略的有效性。
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来源期刊
CiteScore
7.30
自引率
14.60%
发文量
586
审稿时长
6.9 months
期刊介绍: The Journal of The Franklin Institute has an established reputation for publishing high-quality papers in the field of engineering and applied mathematics. Its current focus is on control systems, complex networks and dynamic systems, signal processing and communications and their applications. All submitted papers are peer-reviewed. The Journal will publish original research papers and research review papers of substance. Papers and special focus issues are judged upon possible lasting value, which has been and continues to be the strength of the Journal of The Franklin Institute.
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