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Titlebook: Stability Analysis of Fuzzy-Model-Based Control Systems; Linear-Matrix-Inequa Hak-Keung Lam,Frank Hung-Fat Leung Book 2010 Springer Berlin

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發(fā)表于 2025-3-21 18:14:17 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Stability Analysis of Fuzzy-Model-Based Control Systems
副標(biāo)題Linear-Matrix-Inequa
編輯Hak-Keung Lam,Frank Hung-Fat Leung
視頻videohttp://file.papertrans.cn/876/875264/875264.mp4
概述Presents the state-of-the-art Fuzzy Model based control.Approaches readers unfamiliar with the FMB control systems can follow the material easily by means of various simulation examples, figures and p
叢書名稱Studies in Fuzziness and Soft Computing
圖書封面Titlebook: Stability Analysis of Fuzzy-Model-Based Control Systems; Linear-Matrix-Inequa Hak-Keung Lam,Frank Hung-Fat Leung Book 2010 Springer Berlin
描述In this book, the state-of-the-art fuzzy-model-based (FMB) based control approaches are covered. A comprehensive review about the stability analysis of type-1 and type-2 FMB control systems using the Lyapunov-based approach is given, presenting a clear picture to researchers who would like to work on this field. A wide variety of continuous-time nonlinear control systems such as state-feedback, switching, time-delay and sampled-data FMB control systems, are covered. In short, this book summarizes the recent contributions of the authors on the stability analysis of the FMB control systems. It discusses advanced stability analysis techniques for various FMB control systems, and founds a concrete theoretical basis to support the investigation of FMB control systems at the research level. The analysis results of this book offer various mathematical approaches to designing stable and well-performed FMB control systems. Furthermore, the results widen the applicability of the FMB control approach and help put the fuzzy controller in practice. A wide range of advanced analytical and mathematical analysis techniques will be employed to investigate the system stability and performance of FMB
出版日期Book 2010
關(guān)鍵詞fuzzy control; fuzzy controller; nonlinear control; nonlinear control system; nonlinear system; simulatio
版次1
doihttps://doi.org/10.1007/978-3-642-17844-3
isbn_softcover978-3-642-42296-6
isbn_ebook978-3-642-17844-3Series ISSN 1434-9922 Series E-ISSN 1860-0808
issn_series 1434-9922
copyrightSpringer Berlin Heidelberg 2010
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 23:46:42 | 只看該作者
1434-9922 asily by means of various simulation examples, figures and pIn this book, the state-of-the-art fuzzy-model-based (FMB) based control approaches are covered. A comprehensive review about the stability analysis of type-1 and type-2 FMB control systems using the Lyapunov-based approach is given, presen
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地板
發(fā)表于 2025-3-22 04:36:24 | 只看該作者
Chapter 2 Stability and Performance Conditions for MFSI State-Feedback FMB Control Systems,zy model [101, 102], a nonlinear system can be generally represented as a weighted sum of some local linear systems. The TS fuzzy model provides a systematic and general framework that effectively separates the linear and nonlinear dynamics of the nonlinear plant. This semi-linear property of the TS
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Chapter 6 Regional Switching FMB Control Systems,investigated. Various techniques, such as the MFSI and MFSD approaches with PILF/PDLF, were introduced for relaxing the stability conditions. Under these approaches, a single fuzzy controller is employed for the control process.
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發(fā)表于 2025-3-22 23:33:59 | 只看該作者
Chapter 7 Fuzzy Combined Controller for Nonlinear Systems,of the FMB control systems with imperfectly/perfectly matched premise membership functions are reviewed in Chapter 2. In general, the stability conditions for the FMB based control systems with perfectly matched premise membership functions are more relaxed. However, it is required that the TS fuzzy
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發(fā)表于 2025-3-23 06:58:43 | 只看該作者
Chapter 10 IT2 FMB Control Systems,ework for system analysis and controller synthesis. However, as the membership functions for the type-1 fuzzy sets have limited capability of capturing uncertainty information, the control problem cannot be handled directly if the nonlinear plant is subject to parameter uncertainties. In [18, 88, 89
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