Semi-Global Stabilization of Discrete-Time Linear Systems Subject to Infinite Distributed Input Delays and Actuator Saturations

IF 9.4 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2024-10-11 DOI:10.1109/TCYB.2024.3465437
Yige Guo;Xiang Xu;Lu Liu;Yong Wang;Gang Feng
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Abstract

The semi-global stabilization problem of discrete-time systems subject to infinite distributed input delays and actuator saturations is investigated in this article. This article develops two low-gain feedback control laws for two types of systems, respectively. It is shown that the resulting system is semi-globally exponentially stabilized. Our results include those existing results on systems subject to only input saturations and systems subject to bounded delays and input saturations as special cases. Compared with existing results on infinite delays and actuator saturations, this article develops a more accurate scaling utilizing a more general framework. Furthermore, a novel converse Lyapunov theorem for discrete-time linear infinite-delayed systems and a novel stability analysis theorem for perturbed discrete-time linear infinite-delayed systems are developed to handle the nonlinearity induced by saturations. Finally, this article provides two numerical examples to illustrate the effectiveness of the developed theorems.
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受无限分布式输入延迟和致动器饱和影响的离散时间线性系统的半全局稳定。
本文研究了受无限分布输入延迟和致动器饱和影响的离散时间系统的半全局稳定问题。本文分别为两类系统开发了两种低增益反馈控制律。结果表明,所得到的系统是半全局指数稳定的。我们的结果包括那些仅受输入饱和影响的系统的现有结果,以及作为特例的受有界延迟和输入饱和影响的系统的现有结果。与关于无限延迟和致动器饱和度的现有结果相比,本文利用一个更通用的框架,开发了一种更精确的缩放方法。此外,本文还提出了离散时间线性无限延迟系统的新型反Lyapunov定理和扰动离散时间线性无限延迟系统的新型稳定性分析定理,以处理饱和引起的非线性问题。最后,本文提供了两个数值示例来说明所建立定理的有效性。
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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