Robust Self-Triggered Nonlinear Impulsive Control for Uncertain Systems

IF 8.4 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Mingzhu Wang;Cuiping Lu;Xiaodi Li
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引用次数: 0

Abstract

This article studies the stability problem of uncertain nonlinear systems by self-triggered impulsive control (STIC) methods with nonlinear impulses. With the help of comparison principle, a class of self-triggered mechanisms (STMs) is proposed, where the next triggering instant is given in explicit form with lower communication occupations. Moreover, different from the existing STIC results, the effect of nonlinear impulses is fully considered in the design of STIC strategies in this article, by which the constraints associated with the impulsive control gain can be relaxed. Under such STIC strategies, some sufficient conditions for local asymptotical stability (LAS) of uncertain nonlinear systems are put forward and the estimation of convergence region is provided, with simple structure for easy implementation. In addition, there is no Zeno behavior for the designed STM. Finally, two simulation examples are given to illustrate the validity and advantage of our theoretical results.
不确定系统的鲁棒自触发非线性脉冲控制
本文用非线性脉冲自触发控制方法研究了不确定非线性系统的稳定性问题。利用比较原理,提出了一类自触发机制(STMs),其中下一个触发时刻以较低通信占用的显式形式给出。此外,与已有的STIC结果不同,本文在STIC策略的设计中充分考虑了非线性脉冲的影响,从而可以放松与脉冲控制增益相关的约束。在此策略下,给出了不确定非线性系统局部渐近稳定的若干充分条件,给出了收敛区域的估计,结构简单,便于实现。此外,所设计的STM不存在芝诺行为。最后给出了两个仿真算例,说明了理论结果的有效性和优越性。
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
IEEE Transactions on Systems Man Cybernetics-Systems
IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS
CiteScore
18.50
自引率
11.50%
发文量
812
审稿时长
6 months
期刊介绍: The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.
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