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Titlebook: Robustness in Identification and Control; A. Garulli (Assistant Professor),A. Tesi (Assistan Conference proceedings 1999 Springer-Verlag L

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书目名称Robustness in Identification and Control
编辑A. Garulli (Assistant Professor),A. Tesi (Assistan
视频video
概述The tutorial style makes this an important and accessible book for engineers, control theorists and applied mathematicians.Various real-world case studies are included.All contributions come from worl
丛书名称Lecture Notes in Control and Information Sciences
图书封面Titlebook: Robustness in Identification and Control;  A. Garulli (Assistant Professor),A. Tesi (Assistan Conference proceedings 1999 Springer-Verlag L
描述This book comprises a selection of papers that were first presented at the Robustness in Identification and Control Workshop, held in Siena, July 30 - August 2, 1998. These are the latest contributions to the field, from leading researchers worldwide. The common theme underlying all of the contributions is the interplay between information, uncertainty and complexity in dealing with modelling, identification and control of dynamical systems. Papers cover recent developments in research areas such as identification for control and the classical area of robust control. There are a number of real-world case studies where the most advanced robustness analysis and synthesis techniques are applied to resolve previously unsolved problems. The relevance of the topic to the system engineering field, and the excellent scientific level of the contributions combine to make this book an important acquisition for engineers, control theorists and applied mathematicians.
出版日期Conference proceedings 1999
关键词actuator; control; dynamical systems; identification; mimo system; modeling; optimal control; pole placemen
版次1
doihttps://doi.org/10.1007/BFb0109854
isbn_softcover978-1-85233-179-5
isbn_ebook978-1-84628-538-7Series ISSN 0170-8643 Series E-ISSN 1610-7411
issn_series 0170-8643
copyrightSpringer-Verlag London 1999
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Comments on model validation as set membership identification,chosen model validation test, we may interpret each of these as a set membership identification method. The consequences of such a viewpoint are discussed, and we focus on the important, but perhaps controversial concept of “independence” to make further selections of models within the thus defined sets.
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Modal robust state estimator with deterministic specification of uncertainty, parameters and the noise are individually confined within specified bounds. The basic operations involved in the time and observation updates are examined and the approximations needed to deal with non-linearity, non-convexity and excessive complication of the bounds are considered.
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Modeling and validation of nonlinear feedback systems,sed on linear fractional models. In this paper we discuss the extension of these methods to certain classes of nonlinear models. The Moore-Greitzer model of rotating stall is used as a simple example to illustrate the underlying ideas.
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SM identification of model sets for robust control design from data,. Optimality and convergence results of algorithms for identifying model sets are reported, related to identification problems with different settings of experimental conditions, noise assumptions and norms measuring the system approximation.
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