论无穷维线性状态空间系统的 BIBO 稳定性

IF 2.2 2区数学 Q2 AUTOMATION & CONTROL SYSTEMS

SIAM Journal on Control and Optimization Pub Date : 2024-01-03 DOI:10.1137/23m1563098

Felix L. Schwenninger, Alexander A. Wierzba, Hans Zwart

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引用次数: 0

摘要

SIAM 控制与优化期刊》第 62 卷第 1 期第 22-41 页，2024 年 2 月。摘要本文考虑了由无限维线性状态空间表示法描述的系统的有界输入-有界输出（BIBO）稳定性，填补了迄今为止在这种一般情况下 BIBO 稳定性的正式定义和表征方面的空白。此外，我们还提供了几个保证特定系统 BIBO 稳定性的充分条件，并讨论了在系统的加法和乘法扰动下，这一特性在多大程度上得以保留。

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On BIBO Stability of Infinite-Dimensional Linear State-Space Systems

SIAM Journal on Control and Optimization, Volume 62, Issue 1, Page 22-41, February 2024.
Abstract. In this paper we consider bounded-input-bounded-output (BIBO) stability of systems described by infinite-dimensional linear state-space representations, filling the so far unattended gap of a formal definition and characterization of BIBO stability in this general case. Furthermore, we provide several sufficient conditions guaranteeing BIBO stability of a particular system and discuss to which extent this property is preserved under additive and multiplicative perturbations of the system.

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来源期刊

SIAM Journal on Control and Optimization 数学-应用数学

CiteScore

4.00

自引率

4.50%

发文量

143

审稿时长

12 months

期刊介绍： SIAM Journal on Control and Optimization (SICON) publishes original research articles on the mathematics and applications of control theory and certain parts of optimization theory. Papers considered for publication must be significant at both the mathematical level and the level of applications or potential applications. Papers containing mostly routine mathematics or those with no discernible connection to control and systems theory or optimization will not be considered for publication. From time to time, the journal will also publish authoritative surveys of important subject areas in control theory and optimization whose level of maturity permits a clear and unified exposition. The broad areas mentioned above are intended to encompass a wide range of mathematical techniques and scientific, engineering, economic, and industrial applications. These include stochastic and deterministic methods in control, estimation, and identification of systems; modeling and realization of complex control systems; the numerical analysis and related computational methodology of control processes and allied issues; and the development of mathematical theories and techniques that give new insights into old problems or provide the basis for further progress in control theory and optimization. Within the field of optimization, the journal focuses on the parts that are relevant to dynamic and control systems. Contributions to numerical methodology are also welcome in accordance with these aims, especially as related to large-scale problems and decomposition as well as to fundamental questions of convergence and approximation.