Control of port-Hamiltonian differential-algebraic systems and applications

IF 16.3 1区 数学 Q1 MATHEMATICS
V. Mehrmann, B. Unger
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引用次数: 36

Abstract

We discuss the modelling framework of port-Hamiltonian descriptor systems and their use in numerical simulation and control. The structure is ideal for automated network-based modelling since it is invariant under power-conserving interconnection, congruence transformations and Galerkin projection. Moreover, stability and passivity properties are easily shown. Condensed forms under orthogonal transformations present easy analysis tools for existence, uniqueness, regularity and numerical methods to check these properties. After recalling the concepts for general linear and nonlinear descriptor systems, we demonstrate that many difficulties that arise in general descriptor systems can be easily overcome within the port-Hamiltonian framework. The properties of port-Hamiltonian descriptor systems are analysed, and time discretization and numerical linear algebra techniques are discussed. Structure-preserving regularization procedures for descriptor systems are presented to make them suitable for simulation and control. Model reduction techniques that preserve the structure and stabilization and optimal control techniques are discussed. The properties of port-Hamiltonian descriptor systems and their use in modelling simulation and control methods are illustrated with several examples from different physical domains. The survey concludes with open problems and research topics that deserve further attention.
波特-哈密顿微分代数系统的控制及其应用
讨论了端口-哈密顿广义系统的建模框架及其在数值仿真和控制中的应用。由于该结构在节能互连、同余变换和伽辽金投影下是不变的,因此它是基于自动网络建模的理想结构。此外,稳定性和无源性也很容易显示。正交变换下的凝聚形式提供了简便的存在性、唯一性、正则性分析工具和检验这些性质的数值方法。在回顾一般线性和非线性描述系统的概念后,我们证明了在一般描述系统中出现的许多困难可以在port- hamilton框架内轻松克服。分析了波特-哈密顿广义系统的性质,讨论了时间离散化和数值线性代数技术。为了使广义系统适合于仿真和控制,提出了保持结构的正则化方法。讨论了保持结构稳定的模型简化技术和最优控制技术。通过不同物理域的实例说明了端口-哈密顿广义系统的性质及其在建模、仿真和控制方法中的应用。调查总结了一些有待进一步关注的问题和研究课题。
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来源期刊
Acta Numerica
Acta Numerica MATHEMATICS-
CiteScore
26.00
自引率
0.70%
发文量
7
期刊介绍: Acta Numerica stands as the preeminent mathematics journal, ranking highest in both Impact Factor and MCQ metrics. This annual journal features a collection of review articles that showcase survey papers authored by prominent researchers in numerical analysis, scientific computing, and computational mathematics. These papers deliver comprehensive overviews of recent advances, offering state-of-the-art techniques and analyses. Encompassing the entirety of numerical analysis, the articles are crafted in an accessible style, catering to researchers at all levels and serving as valuable teaching aids for advanced instruction. The broad subject areas covered include computational methods in linear algebra, optimization, ordinary and partial differential equations, approximation theory, stochastic analysis, nonlinear dynamical systems, as well as the application of computational techniques in science and engineering. Acta Numerica also delves into the mathematical theory underpinning numerical methods, making it a versatile and authoritative resource in the field of mathematics.
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