Intelligent Estimation

Jitendra R. Raol received his BE and ME degrees in electrical engineering from M.S. University (MSU) of Baroda, Vadodara, in 1971 and 1973, respectively, and a PhD (in electrical and computer engineering) from McMaster University, Hamilton, Canada, in 1986. He joined the National Aeronautical Laboratory (NAL) in 1975. At CSIR-NAL, he was involved in human pilot modelling in fix- and motion-based research flight simulators. He re-joined NAL in 1986 and retired in July 2007 as Scientist-G (and Head of Flight Mechanics and Control division at CSIR-NAL). He was a fellow of the IEE/IET and a senior member of the IEEE. He is a life-fellow of the Aeronautical Society of India and a life member of the Systems Society of India. Dr. Raol has published nearly 160 research papers and written several books and numerous technical reports. His main research interests include data fusion, system identification, state/parameter estimation, flight mechanics-flight data analysis, H-infinity filtering, nonlinear filtering, artificial neural networks, fuzzy logic systems, genetic algorithms, soft technologies for robotics, and data-systems analytics (DaSyA).Sara Mohan George holds a BTech in electronics and communication from Mahatma Gandhi University, Kerala, India; MTech and PhD degrees from Visvesvaraya Technological University, Karnataka, India. She is currently an Assistant Professor in Ramaiah Institute of Technology, Bangalore, 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. She is also the co-author of Advances in State and Parameter Estimation: Theory and Practice (CRC Press 2025).

• 1. Introduction: Intelligent Estimation. 2. Concepts and Theory of Artificial Neural Networks. 3. System Identification. 4. Filtering and Parameter Estimation. 5. Fuzzy Logic Based Approaches. 6. System Identification and Estimation with Fuzzy Logic/System. 7. Concept and Theory of Genetic Algorithms (GAs). 8. Estimation with Genetic Algorithms (GAs). 9. Hybrid Methods-NN-FL-GA Triad Paradigm. Appendix A. Key Theorems in System Identification, Filtering, and State & Parameter Estimation. Appendix B. Theorem in Soft Computing. Appendix C. Procedure of Building an AI System.