Jitendra R. Raol, Parimala P., Reshma V., Sara M. George

Advances in State and Parameter Estimation (eBook, ePUB)

Theory and Practice

• Format: ePub

Produktbeschreibung

This book deals with the basics of parameter estimation and state estimation as the fundamental building blocks of mathematical modelling activity in the broader field of control theory. All the methods are validated using MATLAB®-based implementations with realistically simulated data for general dynamic systems, as well as for aircraft parameter estimation. This book includes several illustrative examples and chapter-end exercises.

Features:

• Provides comprehensive coverage of all issues related to parameter and state estimation.
• Discusses advanced topics related to Kalman filter, stability analysis, image centroid tracking and neural networks for parameter estimation.
• Explores convergence and stability results for the discussed methods.
• Reviews the estimation of parameters in linear/nonlinear models, and distributed fitting.
• Includes MATLAB®-based illustrative examples, and exercises.

This book is aimed at researchers and graduate students in systems and control, signal processing, estimation theory, engineering mathematics, and aerospace engineering.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Erscheinungstermin: 27. Mai 2025
• Englisch
• ISBN-13: 9781040349960
• Artikelnr.: 73816931

Autorenporträt

Jitendra R. Raol received BE and ME degrees in electrical engineering from M. S. University (MSU) of Baroda, Vadodara, in 1971 and 1973, respectively, and PhD (electrical & computer engineering) from McMaster University, Hamilton, Canada, in 1986; at both universities he was also a postgraduate research and teaching assistant. He joined the National Aeronautical Laboratory (NAL, Bangalore) in 1975. At CSIR-NAL he was involved with human pilot modelling activities in fix- and motion-based research flight simulators. He rejoined NAL in 1986 and retired in July 2007 as Scientist-G (and Head at the Flight Mechanics and Control Division at CSIR-NAL).

Parimala P. earned her PhD degree from Jain University, Karnataka, India in 2018 under the guidance of Dr. J. R. Raol, NAL, Bangalore. Her thesis was titled Image Tracking and Fusion using Square Root Information Filter. She earned her BE in Telecommunication Engineering and ME degree in Digital Communication Engineering from BMS College of Engineering, Bangalore University, Bangalore during the year 1996 and 1999, respectively. She has published several research papers in international & national journals and conferences.

Reshma V. completed her doctoral studies at Jain University, Karnataka, India in 2018, focusing on the development of a 'Fuzzy Augmented H-I Filter for Target Tracking'. She had obtained her M.Tech degree in Power Electronics from Visvesvaraya Technological University (VTU) in 2005. Throughout her career, she has made significant contributions to academia and research, publishing numerous papers in both international and national journals and conferences. Her research interests span across artificial intelligence, embedded system design, and VLSI.

Sara M. George holds a B. Tech in Electronics and Communication from Mahatma Gandhi University, Kerala; M. Tech and PhD degrees from Visvesvaraya Technological University, Karnataka. Her research interests include nonlinear filtering, signal processing and embedded system design. She has published nearly 20 technical papers in various conferences and journals.

Inhaltsangabe

1. Introduction 2. Least Squares and Maximum
Likelihood Methods 3. Kalman Filtering Methods 4. Filtering
cum
Data Fusion with State Delay and Missing Measurements 5. Gaussian
Sum Extended Kalman Filter with Lyapunov Stability Analysis 6. Gaussian
sum Information Filter with Lyapunov Stability Analysis 7. Image Centroid Tracking with Square
Root Kalman Filters 8. Image Centroid Tracking with Fuzzy
Logic
Augmented Filters 9. Image Centroid Tracking
cum
Fusion using New Factorization Filtering Algorithms 10. H
Infinity Fuzzification Filtering and Target Tracking (TT) 11. H
Infinity
Based Observer 12. Deterministic Nonlinear Estimators
Observers and Stability Results 13. Hybrid Global H
Infinity Filter 14. Neural Networks for Parameter Estimation with Lyapunov Stability 15. Interactive Multiple Modelling for Target Tracking with New Algorithms 16. Machine Learning for Estimation Appendix A Appendix B Appendix C