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Titlebook: Neural Network-Based State Estimation of Nonlinear Systems; Application to Fault Heidar A. Talebi,Farzaneh Abdollahi,Khashayar Khor Book 20

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發(fā)表于 2025-3-21 17:40:49 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Neural Network-Based State Estimation of Nonlinear Systems
副標(biāo)題Application to Fault
編輯Heidar A. Talebi,Farzaneh Abdollahi,Khashayar Khor
視頻videohttp://file.papertrans.cn/664/663692/663692.mp4
概述Presents both the Linear-in-Parameter Neural Network based observer and the Nonlinear-in-Parameter Neural Network based observer approaches to nonlinear systems.Discusses the neural network structure
叢書(shū)名稱Lecture Notes in Control and Information Sciences
圖書(shū)封面Titlebook: Neural Network-Based State Estimation of Nonlinear Systems; Application to Fault Heidar A. Talebi,Farzaneh Abdollahi,Khashayar Khor Book 20
描述."Neural Network-Based State Estimation of Nonlinear Systems" presents efficient, easy to implement neural network schemes for state estimation, system identification, and fault detection and Isolation with mathematical proof of stability, experimental evaluation, and Robustness against unmolded dynamics, external disturbances, and measurement noises..
出版日期Book 2010
關(guān)鍵詞actuator; fault detection; identification; linear optimization; neural network; nonlinear system; robot; st
版次1
doihttps://doi.org/10.1007/978-1-4419-1438-5
isbn_softcover978-1-4419-1437-8
isbn_ebook978-1-4419-1438-5Series ISSN 0170-8643 Series E-ISSN 1610-7411
issn_series 0170-8643
copyrightSpringer-Verlag New York 2010
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 22:35:04 | 只看該作者
板凳
發(fā)表于 2025-3-22 01:19:36 | 只看該作者
An Actuator Fault Detection and Isolation Scheme: Experiments in Robotic Manipulators,nment impacts. Consequently, an exceptional level of autonomy is required in these types of applications. Hence, there is a high demand for new methods in supervision, fault detection, fault isolation, and fault recovery.
地板
發(fā)表于 2025-3-22 05:03:24 | 只看該作者
Neural Network-Based State Estimation Schemes,e-modification term added to guarantee the robustness of the observer. The stability of the recurrent neural network observers are shown by Lyapunov’s direct method. Moreover, the strictly positive real (SPR) assumption imposed on the output error equation is relaxed.
5#
發(fā)表于 2025-3-22 12:28:54 | 只看該作者
0170-8643 to nonlinear systems.Discusses the neural network structure ."Neural Network-Based State Estimation of Nonlinear Systems" presents efficient, easy to implement neural network schemes for state estimation, system identification, and fault detection and Isolation with mathematical proof of stability,
6#
發(fā)表于 2025-3-22 14:11:54 | 只看該作者
Book 2010m identification, and fault detection and Isolation with mathematical proof of stability, experimental evaluation, and Robustness against unmolded dynamics, external disturbances, and measurement noises..
7#
發(fā)表于 2025-3-22 21:06:41 | 只看該作者
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發(fā)表于 2025-3-22 22:00:38 | 只看該作者
Heidar A. Talebi,Farzaneh Abdollahi,Rajni V. Patel,Khashayar Khorasani of milliseconds. Most of the power in interplanetary waves and turbulence lies at hydromagnetic scales. These fluctuations are normally of large amplitude, containing enough energy to affect solar and galactic cosmic rays, and may be the remnants of a coronal turbulence field powerful enough to pla
9#
發(fā)表于 2025-3-23 03:30:11 | 只看該作者
Heidar A. Talebi,Farzaneh Abdollahi,Rajni V. Patel,Khashayar Khorasanis. Solar minimum conditions are characterized by the presence of only a few plage regions, which dominate X-ray emission below 20 ?. Activity events under these conditions can cause a large increase in flux below 20 ? in coincidence with a decrease in emission between 44 and 60 ?, as the silicon and
10#
發(fā)表于 2025-3-23 07:00:37 | 只看該作者
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