This book deals with basics of parameter estimation and state estimation as the 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. It includes several illustrative examples and exercises.
This book deals with basics of parameter estimation and state estimation as the 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. It includes several illustrative examples and exercises.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Jitendra R. Raol received B. E. and M. E. degrees in electrical engineering from M. S. University (MSU) of Baroda, Vadodara, in 1971 and 1973 respectively and Ph.D. (electrical & computer engineering) from McMaster University, Hamilton, Canada, in 1986, and at both the places he was also a post graduate research and teaching assistant. He joined the National Aeronautical Laboratory (NAL, Bangalore, India) in 1975. At CSIR-NAL he was involved in the activities on human pilot modeling in fix- and motion-based research flight simulators. He re-joined NAL in 1986 and retired in July 2007 as Scientist-G (and Head, flight mechanics and control division at CSIR-NAL). Parimala P. works as Assistant Professor at Ramaiah Institute of Technology, India in the Department of Electronics and Telecommunication Engineering. She 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. works as Assistant Professor in the Department of Electronics and Communication Engineering at Ramaiah Institute of Technology, India. She 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 is Assistant Professor in Ramaiah Institute of Technology, Bangalore, India. She holds B. Tech in Electronics and Communication from Mahatma Gandhi University, Kerala, India; M. Tech and Ph. D. degrees from Visvesvaraya Technological University, Karnataka, India. 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 analyses 15. Interactive Multiple Modelling for Target Tracking with New Algorithms 16. Machine Learning for Estimation Appendix A Appendix B Appendix C
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 analyses 15. Interactive Multiple Modelling for Target Tracking with New Algorithms 16. Machine Learning for Estimation Appendix A Appendix B Appendix C
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