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Title
Fault estimation for network systems via intermediate estimator / Jun-Wei Zhu, Xin Wang, Guang-Hong Yang.
ISBN
9789811963216 (electronic bk.)
9811963215 (electronic bk.)
9789811963209
9811963207
Published
Singapore : Springer, 2022.
Language
English
Description
1 online resource : illustrations (black and white, and color).
Item Number
10.1007/978-981-19-6321-6 doi
Call Number
QA76.9.F38
Dewey Decimal Classification
004.2
Summary
This book is concerned with the fault estimation problem for network systems. Firstly, to improve the existing adaptive fault estimation observer, a novel so-called intermediate estimator is proposed to identify the actuator or sensor faults in dynamic control systems with high accuracy and convergence speed. On this basis, by exploiting the properties of network systems such as multi-agent systems and large-scale interconnected systems, this book introduces the concept of distributed intermediate estimator; faults in different nodes can be estimated simultaneously; meanwhile, satisfactory consensus performances can be obtained via compensation based protocols. Finally, the characteristics of the new fault estimation methodology are verified and discussed by a series of experimental results on networked multi-axis motion control systems. This book can be used as a reference book for researcher and designer in the field of fault diagnosis and fault-tolerant control and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities. .
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Source of Description
Description based on print version record.
Chapter 1. Introduction
Chapter 2. Design of nominal intermediate estimator
Chapter 3. Robust Fault Estimation (FE) for a Network of Dynamical Systems
Chapter 4. FE based Tracking Control for Multi-Agent Systems (MASs) with undirected graph
Chapter 5. FE based Tracking Control for MASs under directed graph
Chapter 6. FE based Tracking Control for MASs with mismatched disturbances
Chapter 7. Applications on Multi-Axis Motion Control Systems
Chapter 8. Conclusions and Future Research Directions.