Recursive Filtering for 2-D Shift-Varying Systems with Communication Constraints
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Covers recent advances of recursive filtering for 2-D shift-varying systems subjected to communication constraints from the engineering perspective.
Includes the recursive filter design, resilience operation and performance analysis for the considered 2-D shift-varying systems.
Captures the essence of the design for 2-D recursive filters.
Develops a series of latest results about the robust Kalman filtering and protocol-based filtering.
Analyzes recursive filter design and filtering performance for the considered systems.
This book aims at graduate students and researchers in mechanical engineering, industrial engineering, communications networks, applied mathematics, robotics and control systems.
Forlag: Taylor & Francis Ltd
Format: 23 x 16 cm
- Kommunikasjonsteknikk / telekommunikasjon
- Automatisk styrings- og reguleringsteknikk
- Energi, kraftproduksjon, -distribusjon, og -lagring
1.1 2-D Systems
1.2 Communication Constraints
1.3 Recent Progress on Filtering for 2-D Systems
2. Minimum-Variance Recursive Filtering for Two-Dimensional Systems with Degraded Measurements: Boundedness and Monotonicity
2.1 Problem Formulation
2.2 The Minimum-Variance Filter Design
2.3 Performance Analysis
2.4 Numerical Example
3. Robust Kalman Filtering for Two-Dimensional Systems with Multiplicative Noises and Measurement Degradations
3.1 Problem Formulation and Preliminaries
3.2 Upper Bound for The Generalized Error Variance
3.3 Suboptimal Filter Design
3.4 Numerical Example
4. Robust Finite-Horizon Filtering for Two-Dimensional Systems with Randomly Varying Sensor Delays
4.1 Problem Formulation
4.3 Finite-Horizon Robust Kalman Filter Design
4.4 Numerical Example
5. Recursive Filtering for Two-Dimensional Systems with Missing Measurements subject to Uncertain Probabilities
5.1 Problem Formulation
5.2 Recursive Filter Design
5.3 Numerical Example
6. Resilient State Estimation for Two-Dimensional Shift-Varying Systems with Redundant Channels
6.1 Problem Formulation and Preliminaries
6.2 Resilient Filter Design
6.3 Numerical Examples
7. Recursive Distributed Filtering for Two-Dimensional Shift-Varying Systems Over Sensor Networks Under Random Access Protocols
7.1 Problem Formulation and Preliminaries
7.2 Main Results
7.3 Numerical Example
8. Resilient Filtering for Linear Shift-Varying Repetitive Processes under Uniform Quantizations and Round-Robin Protocols
8.1 Problem Formulation
8.2 Main Results
8.3 Numerical Example
9. Event-Triggered Recursive Filtering for Shift-Varying Linear Repetitive Processes
9.1 Problem Formulation
9.2 Main Results
9.3 Numerical Example
10. Conclusions and Future Topics
Professor Liang’s research interests include two-dimensional systems, stochastic systems, complex networks, robust filtering and bioinformatics. She has published around 90 papers in refereed international journals. According to the Web of Science, her publications have received more than 3000 citations with h-index 36. She has served (or is serving) as an Associate Editor for IEEE Transactions on Neural Networks and Learning Systems, International Journal of Computer Mathematics, IET Control Theory & Applications, Neurocomputing. She is also a member of the program committees of more than 20 international conferences, and serves as a very active reviewer for many international journals.
Zidong Wang is currently a Professor of Department of Computer Science at Brunel University London in the United Kingdom. From January 1997 to December 1998, he was an Alexander von Humboldt research fellow with the Control Engineering Laboratory, Ruhr-University Bochum, Germany. From January 1999 to February 2001, he was a Lecturer with the Department of Mathematics, University of Kaiserslautern, Germany. From March 2001 to July 2002, he was a University Senior Research Fellow with the School of Mathematical and Information Sciences, Coventry University, U.K. In August 2002, he joined the Department of Information Systems and Computing, Brunel University, U.K., as a Lecturer, and was then promoted to a Reader in September 2003 and to a Chair Professor in July 2007.
Professor Wang’s research interests include dynamical systems, signal processing, bioinformatics, control theory and applications. He has published more than 200 papers in refereed international journals. According to the Web of Science, his publications have received more than 8000 citations (excluding self-citations) with h-index 48. He was awarded the Humboldt research fellowship in 1996 from Alexander von Humboldt Foundation, the JSPS Research Fellowship in 1998 from Japan Society for the Promotion of Science, and the William Mong Visiting Research Fellowship in 2002 from The University of Hong Kong. Professor Wang is an IEEE Fellow for his contributions to networked control and complex networks. He serves (or has served) as the Editor-in-Chief for Neurocomputing, Deputy Editor-in-Chief for International Journal of Systems Science, an Action Editor for Neural Networks, an Associate Editor for 12 international journals including IEEE Transactions on Automatic Control, IEEE Transactions on Neural Networks, IEEE Transactions on Signal Processing, IEEE Transactions on Systems, Man, and Cybernetics-Part C, IEEE Transactions on Control Systems Technology, Circuits, Systems & Signal Processing, Asian Journal of Control, an Editorial Board Member for IET Control Theory and Applications, International Journal of Computer Mathematics, International Journal of General Systems, and an Associate Editor on the Conference Editorial Board for the IEEE Control Systems Society. He is a Fellow of the Royal Statistical Society, a member of program committee for many international conferences, and a very active reviewer for many international journals. He was nominated an appreciated reviewer for IEEE Transactions on Signal Processing in 2006-2008 and 2011, an appreciated reviewer for IEEE Transactions on Intelligent Transportation Systems in 2008; an outstanding reviewer for IEEE Transactions on Automatic Control in 2004 and for the journal Automatica in 2000.
Fan Wang received the B.Sc. degree in mathematics from Hefei Normal University in 2012, and the Ph.D. degree in applied mathematics from Southeast University, Nanjing, China, in 2018. From 2016 to 2018, she was a visiting Ph.D. student with the Department of Information Systems and Computing, Brunel University London, Uxbridge, U.K. She was a Research Associate with the Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, in 2019, for two months. She is currently a Postdoctoral Research Fellow with the School of Automation, Southeast University, Nanjing, China.
Dr. Wang has published over 20 papers in refereed international journals. Her current research interests include stochastic systems, two-dimensional systems, time-varying systems, optimal control and robust filtering. She is a very active reviewer for several international journals.