Overview
- 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 for fault detection actuators using an application to satellite attitude control systems and robotic manipulators
- Discusses robust sensor and actuator fault detection and estimation
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Control and Information Sciences (LNCIS, volume 395)
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Table of contents (6 chapters)
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Front Matter
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Back Matter
Keywords
About this book
"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.
Authors and Affiliations
Bibliographic Information
Book Title: Neural Network-Based State Estimation of Nonlinear Systems
Book Subtitle: Application to Fault Detection and Isolation
Authors: Heidar A. Talebi, Farzaneh Abdollahi, Rajni V. Patel, Khashayar Khorasani
Series Title: Lecture Notes in Control and Information Sciences
DOI: https://doi.org/10.1007/978-1-4419-1438-5
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag New York 2010
Softcover ISBN: 978-1-4419-1437-8Published: 14 December 2009
eBook ISBN: 978-1-4419-1438-5Published: 04 December 2009
Series ISSN: 0170-8643
Series E-ISSN: 1610-7411
Edition Number: 1
Number of Pages: XIX, 154
Number of Illustrations: 100 b/w illustrations
Topics: Control and Systems Theory, Robotics and Automation, Mathematical and Computational Engineering, Vibration, Dynamical Systems, Control, Systems Theory, Control, Control, Robotics, Mechatronics