Model-based Health Monitoring of Hybrid Systems Model-based Health Monitoring of Hybrid Systems

Model-based Health Monitoring of Hybrid Systems

Danwei Wang and Others
    • 87,99 €
    • 87,99 €

Publisher Description

This book systematically presents a comprehensive framework and effective techniques for in-depth analysis, clear design procedure, and efficient implementation of diagnosis and prognosis algorithms for hybrid systems. It offers an overview of the fundamentals of diagnosis\prognosis and hybrid bond graph modeling. This book also describes hybrid bond graph-based quantitative fault detection, isolation and estimation. Moreover, it also presents strategies to track the system mode and predict the remaining useful life under multiple fault condition. A real world complex hybrid system—a vehicle steering control system—is studied using the developed fault diagnosis methods to show practical significance.
Readers of this book will benefit from easy-to-understand fundamentals of bond graph models, concepts of health monitoring, fault diagnosis and failure prognosis, as well as hybrid systems.  The reader will gain knowledge of fault detection and isolation in complex systems including those with hybrid nature, and will learn state-of-the-art developments in theory and technologies of fault diagnosis and failure prognosis for complex systems.

GENRE
Computing & Internet
RELEASED
2013
23 May
LANGUAGE
EN
English
LENGTH
309
Pages
PUBLISHER
Springer New York
SIZE
7.6
MB

More Books by Danwei Wang, Ming Yu, Chang Boon Low & Shai Arogeti

Collaborative Fleet Maneuvering for Multiple Autonomous Vehicle Systems Collaborative Fleet Maneuvering for Multiple Autonomous Vehicle Systems
2022
Collaborative Perception, Localization and Mapping for Autonomous Systems Collaborative Perception, Localization and Mapping for Autonomous Systems
2020
Satellite Formation Flying Satellite Formation Flying
2016
Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation
2014