Multi-model Jumping Systems: Robust Filtering and Fault Detection (PDF)
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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.
His current research interests include control theory & control systems; systems modeling, methods & applications; signal processing and artificial intelligence. He has co-authored a book on stochastic systems and authored or co-authored over 100 papers in professional journals, conference proceedings and technical reports.
Xiaoli Luan is Full Professor at the School of Internet of Things Engineering Jiangnan University, Wuxi, China, since 2017. From 2010 to 2011, she was Visiting Scholar at the University of Victoria, Australia. She was a recipient of the National Excellent Youth Funds Award and the "six talent peaks" Award of Jiangsu Province. Her current research interests include complex dynamic system modeling, advanced control and optimization, industrial big data analysis and applications, data mining and machine learning. She has authored or co-authored over 60 papers in professional journals, conference proceedings and technical reports.
- Autoren: Shuping He , Xiaoli Luan
- 2021, 1st ed. 2021, 182 Seiten, Englisch
- Verlag: Springer Nature Singapore
- ISBN-10: 9813364742
- ISBN-13: 9789813364745
- Erscheinungsdatum: 01.03.2021
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