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Titlebook: Differential Linear Matrix Inequalities; In Sampled-Data Syst José C. Geromel Book 2023 The Editor(s) (if applicable) and The Author(s), un

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书目名称Differential Linear Matrix Inequalities
副标题In Sampled-Data Syst
编辑José C. Geromel
视频videohttp://file.papertrans.cn/279/278780/278780.mp4
概述Describes a new mathematical tool named differential linear matrix inequality (DLMI) and its applications.Presents and discusses a numerical determination of a solution whenever it exists.Includes cov
图书封面Titlebook: Differential Linear Matrix Inequalities; In Sampled-Data Syst José C. Geromel Book 2023 The Editor(s) (if applicable) and The Author(s), un
描述This book is entirely devoted to sampled-data control systems analysis and design from a new point of view, which has at its core a mathematical tool named Differential Linear Matrix Inequality - DLMI, a natural generalization of Linear Matrix Inequality - LMI, that had an important and deep impact on systems and control theory almost thirty years ago. It lasts until now. It is shown that the DLMI is well adapted to deal with the important class of sampled-data control systems in both theoretical and numerical contexts. All design conditions are expressed by convex programming problems, including when robustness against parameter uncertainty is assessed and imposed through state feedback control..Special attention is given to filter, dynamic output feedback and model predictive control design, as well as nonlinear systems of Lur’e class and Markov jump linear systems. .The subject is treated with mathematical rigor, at the same time, trying to keep the reading agreeable and fruitful for colleagues and students. To this respect, the book contains together with the theoretical developments, many solved illustrative examples and the formulation of some open problems that could be face
出版日期Book 2023
关键词Differential Linear Matrix Inequalities; Convex Optimization; Robustness in control; Sampled-data Syste
版次1
doihttps://doi.org/10.1007/978-3-031-29754-0
isbn_softcover978-3-031-29756-4
isbn_ebook978-3-031-29754-0
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Sampled-Data Control Systems,nst parameter uncertainty is concerned. This important aspect is left to be treated with details in the forthcoming chapters. The state space realization of the open-loop system is introduced together with the sampled-data control structure. As usual, conditions for sampled-data systems stability ar
发表于 2025-3-22 05:19:14 | 显示全部楼层
Filtering and Control,hapters some aspects involving this important performance index, now our goal is to tackle some other aspects related to norm and convex bounded parameter uncertainty. To this end, in a first step of analysis, we need to express the objective function and the optimal design problems through DLMIs. S
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Filtering and Control,e with model and parameter uncertainty of the important norm bounded class. Our intention is to present this theory but restricted to the framework of sampled-data systems. Several aspects of analysis and control and filtering design are presented and discussed in detail, given particular attention
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Markov Jump Linear Systems, MJLS models adequately, with precision, many practical applications of particular interest and importance. Nevertheless, concerning sampled-data control of MJLS, very few results are available in the literature. This chapter aims to design linear filters and controllers in both contexts of . and .
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Nonlinear Systems Control,the particular but important class of nonlinear systems known as Lur’e systems, which is fully characterized in the literature and in the very beginning of this chapter. The results reported afterward may have a useful impact in sampled-data control systems due to the use of the ideas that stemmed f
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Model Predictive Control,formed in the Bibliography notes, it has been successfully applied to many systems of practical importance. One of the main reasons for that success is the fact that MPC is able to cope with state and control variable constraints. Hence, our main purpose is to generalize the previous state feedback
发表于 2025-3-23 02:40:18 | 显示全部楼层
Numerical Experiments,es introduced in the previous chapters of this book. In fact, the designed control will not be practically implemented but numerically simulated, in order to evaluate stability, robustness, performance and the impact that the sampling period magnitude has on those important attributes of the closed-
发表于 2025-3-23 05:36:16 | 显示全部楼层
https://doi.org/10.1007/978-3-031-29754-0Differential Linear Matrix Inequalities; Convex Optimization; Robustness in control; Sampled-data Syste
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