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Multi-model jumping systemsrobust fi...

He, Shuping.

Multi-model jumping systemsrobust filtering and fault detection /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Multi-model jumping systemsby Shuping He, Xiaoli Luan.
其他題名:	robust filtering and fault detection /
作者:	He, Shuping.
其他作者:	Luan, Xiaoli.
出版者:	Singapore :Springer Singapore :2021.
面頁冊數:	xiii, 182 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Engineering mathematics.
電子資源:	https://doi.org/10.1007/978-981-33-6474-5
ISBN:	9789813364745$q(electronic bk.)

Multi-model jumping systemsrobust filtering and fault detection /
He, Shuping.

Multi-model jumping systemsrobust filtering and fault detection /[electronic resource] :by Shuping He, Xiaoli Luan. - Singapore :Springer Singapore :2021. - xiii, 182 p. :ill., digital ;24 cm.

Introduction -- Robust Filtering -- Robust filtering for jumping systems -- Finite-time robust filtering for jumping systems -- Finite-frequency robust filtering for jumping systems -- Higher order moment robust filtering for jumping systems -- Fault Detection -- Robust fault detection for jumping systems -- Observer-based robust fault detection for fuzzy jumping systems -- Filtering-based robust fault detection of fuzzy jumping systems -- Neural network-based robust fault detection for nonlinear jumping systems -- Conclusion.

This book focuses on multi-model systems, describing how to apply intelligent technologies to model complex multi-model systems by combining stochastic jumping system, neural network and fuzzy models. It focuses on robust filtering, including finite-time robust filtering, finite-frequency robust filtering and higher order moment robust filtering schemes, as well as fault detection problems for multi-model jump systems, such as observer-based robust fault detection, filtering-based robust fault detection and neural network-based robust fault detection methods. The book also demonstrates the validity and practicability of the theoretical results using simulation and practical examples, like circuit systems, robot systems and power systems. Further, it introduces readers to methods such as finite-time filtering, finite-frequency robust filtering, as well as higher order moment and neural network-based fault detection methods for multi-model jumping systems, allowing them to grasp the modeling, analysis and design of the multi-model systems presented and implement filtering and fault detection analysis for various systems, including circuit, network and mechanical systems.

ISBN: 9789813364745$q(electronic bk.)

Standard No.: 10.1007/978-981-33-6474-5doiSubjects--Topical Terms:

182072
Engineering mathematics.

LC Class. No.: TA330

Dewey Class. No.: 620.00151

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505 0 $a Introduction -- Robust Filtering -- Robust filtering for jumping systems -- Finite-time robust filtering for jumping systems -- Finite-frequency robust filtering for jumping systems -- Higher order moment robust filtering for jumping systems -- Fault Detection -- Robust fault detection for jumping systems -- Observer-based robust fault detection for fuzzy jumping systems -- Filtering-based robust fault detection of fuzzy jumping systems -- Neural network-based robust fault detection for nonlinear jumping systems -- Conclusion.
520 $a This book focuses on multi-model systems, describing how to apply intelligent technologies to model complex multi-model systems by combining stochastic jumping system, neural network and fuzzy models. It focuses on robust filtering, including finite-time robust filtering, finite-frequency robust filtering and higher order moment robust filtering schemes, as well as fault detection problems for multi-model jump systems, such as observer-based robust fault detection, filtering-based robust fault detection and neural network-based robust fault detection methods. The book also demonstrates the validity and practicability of the theoretical results using simulation and practical examples, like circuit systems, robot systems and power systems. Further, it introduces readers to methods such as finite-time filtering, finite-frequency robust filtering, as well as higher order moment and neural network-based fault detection methods for multi-model jumping systems, allowing them to grasp the modeling, analysis and design of the multi-model systems presented and implement filtering and fault detection analysis for various systems, including circuit, network and mechanical systems.
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