文章基本信息

标题：IQClab: A new IQC based toolbox for robustness analysis and control design ⁎
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作者：Joost Veenman ; Carsten W. Scherer ; Carlos Ardura 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：8
页码：69-74
DOI：10.1016/j.ifacol.2021.08.583
语种：English
出版社：Elsevier
摘要：AbstractIn this paper we present our new integral quadratic constraint (IQC) based toolbox, named IQClab. The toolbox is a versatile extension of the MATLAB Robust Control Toolbox and offers a wide range of possibilities for performing robustness analysis and control design for a large class of uncertain and linear parameter varying (LPV) systems. In addition, IQClab consists of an extensive set of auxiliary tools and functions for performing model reduction, implementing control switching schemes, generating performance weighting functions, among others. Not only is the toolbox easy to use, but it also has a modular build and can be applied in combination with different parsers and solvers. This allows developers to seamlessly include new linear matrix inequality (LMI) and IQC based algorithms as well as other extensions. The aim of the present paper is to provide an overview of the toolbox’s capabilities together with some demonstrations and illustrative numerical examples.
关键词：KeywordsIntegral quadratic constraints (IQCs)linear matrix inequalities (LMIs)uncertain systemslinear parameter varying (LPV) systemsrobustness analysiscontrol designtoolbox