Neural network-based state estimation of nonlinear systems : application to fault detection and isolation /
Annotation
| Other Authors: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
New York ; London :
Springer,
©2010
New York ; London : c2010 |
| Series: | Lecture notes in control and information sciences ;
395 |
| Subjects: |
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| 245 | 0 | 0 | |a Neural network-based state estimation of nonlinear systems : |b application to fault detection and isolation / |c Heidar A. Talebi [and others] |
| 260 | |a New York ; |a London : |b Springer, |c ©2010 | ||
| 264 | 1 | |a New York ; |a London : |b Springer, |c c2010 | |
| 300 | |a 1 online resource (xix, 154 p.) : |b ill | ||
| 300 | |a 1 online resource (xix, 154 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 490 | 1 | |a Lecture notes in control and information sciences, |x 0170-8643 ; |v 395 | |
| 500 | |a Description based on print version record | ||
| 504 | |a Includes bibliographical references (p. 147-152) and index | ||
| 504 | |a Includes bibliographical references and index | ||
| 505 | 0 | |a Introduction -- Neural network-based state estimation schemes -- Neural network-based system identification schemes -- An actuator fault detection and isolation scheme : experiments in robotic manipulators -- A robust actuator gain fault detection and isolation scheme -- A robust sensor and actuator fault detection and estimation approach -- Appendix A: Preliminary definitions -- Appendix B: Flexible-joint manipulator model -- Appendix C: Neural network learning rules for theorem 6.1 -- Stability conditions of theorem 6.1-part 2 | |
| 505 | 0 | |a Introduction -- Observation (LPNN and NPNN) -- Identification (LPNN and NPNN) -- Actuator Fault Detection and Isolation: Experiments in Robotic Manipulators -- A Robust Actuator Gain Fault Detection and Isolation Scheme -- A Robust Sensor and Actuator Fault Detection and Estimation: Application to a Satellite's Attitude Control Subsystem -- Preliminary Definitions -- Neural Network Learning Rules for Theorem 6.1 -- Stability Conditions of Theorem 6.1-Part 2 | |
| 506 | |a License restrictions may limit access | ||
| 520 | 8 | |a Annotation |b "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 | |
| 588 | |a Description based on print version record | ||
| 588 | 0 | |a Print version record | |
| 596 | |a 22 | ||
| 650 | 0 | |a Control theory | |
| 650 | 0 | |a Fault location (Engineering) | |
| 650 | 0 | |a Neural networks (Computer science) | |
| 650 | 0 | |a Nonlinear systems | |
| 650 | 4 | |a Control Theory | |
| 650 | 4 | |a Dynamic Testing | |
| 650 | 4 | |a Neural Networks (Computer Science) | |
| 650 | 4 | |a Nonlinear Systems | |
| 650 | 7 | |a Control theory |2 fast | |
| 650 | 7 | |a Fault location (Engineering) |2 fast | |
| 650 | 7 | |a Ingénierie |2 eclas | |
| 650 | 7 | |a Ingénierie |2 eclas | |
| 650 | 7 | |a Neural networks (Computer science) |2 fast | |
| 650 | 7 | |a Nonlinear systems |2 fast | |
| 655 | 4 | |a Electronic books | |
| 700 | 1 | |a Talebi, H. A., |d 1965- |1 http://viaf.org/viaf/45181896 | |
| 700 | 1 | |a Talebi, H. A., |d 1965- | |
| 776 | 0 | 8 | |i Print version: |t Neural network-based state estimation of nonlinear systems |d New York ; London : Springer, c2010 |z 9781441914378 |z 1441914374 |z 9781441914385 |z 1441914382 |w (DLC) 2009940450 |w (OCoLC)ocn434563461 |
| 776 | 0 | 8 | |i Print version: |t Neural network-based state estimation of nonlinear systems |d New York ; London : Springer, ©2010 |z 9781441914378 |z 1441914374 |w (OCoLC)434563461 |
| 776 | 0 | 8 | |i Print version: |t Neural network-based state estimation of nonlinear systems |d New York ; London : Springer, ©2010 |z 9781441914378 |z 1441914374 |w (OCoLC)434563461 |
| 830 | 0 | |a Lecture notes in control and information sciences ; |v 395 | |
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