基于可切换指数的非线性系统快速收敛的预定义时间准滑动模式控制

IF 5.3 1区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Chaos Solitons & Fractals Pub Date : 2024-08-24 DOI:10.1016/j.chaos.2024.115423
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引用次数: 0

摘要

本文提出了一种新的非线性系统预定时间非奇异滑模控制(SMC)方法。首先,根据预定时间稳定性(PTS)的定义,设计了一个新的充分条件,以确保系统状态在预定时间内收敛到原点。通过设计一个简单的可变指数,不仅保证了 PTS,还能在系统状态远离和接近平衡点时进行自适应调整。而且与传统方法相比,无论系统状态远离平衡点还是接近平衡点,所提出的定理 2 都能增强控制效果,实现更快的收敛。其次,基于所提出的稳定性条件,设计了一种新的非奇异 SMC 方法,以确保跟踪误差在预定时间内收敛到任意小的区域。最后,通过仿真和物理实验验证了所提出方法的良好性能。
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Predefined time quasi-sliding mode control with fast convergence based on a switchable exponent for nonlinear systems

This paper proposed a new predefined time nonsingular sliding mode control (SMC) method for nonlinear systems. Firstly, based on the definition of predefined time stability (PTS), a new sufficient condition is designed to ensure that the system states converge to the origin within a predefined time. The design of a simple variable exponent not only guarantees PTS, but also enables adaptive adjustment when the system states are far away from and near the equilibrium point. And compared with traditional methods, the proposed Lemma 2 enhances the control effect and achieves faster convergence whether the system states are far from or near to the equilibrium point. Secondly, based on the proposed stability condition, a new nonsingular SMC method is designed to ensure that the tracking error converges to an arbitrarily small region within a predefined time. Finally, the proposed method is verified to have good performance through simulation and physical experiments.

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来源期刊
Chaos Solitons & Fractals
Chaos Solitons & Fractals 物理-数学跨学科应用
CiteScore
13.20
自引率
10.30%
发文量
1087
审稿时长
9 months
期刊介绍: Chaos, Solitons & Fractals strives to establish itself as a premier journal in the interdisciplinary realm of Nonlinear Science, Non-equilibrium, and Complex Phenomena. It welcomes submissions covering a broad spectrum of topics within this field, including dynamics, non-equilibrium processes in physics, chemistry, and geophysics, complex matter and networks, mathematical models, computational biology, applications to quantum and mesoscopic phenomena, fluctuations and random processes, self-organization, and social phenomena.
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