Parameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system dynamics. The assumed model consists of a finite set of parameters, the values of which are calculated using estimation techniques. Most of the techniques that exist are based on least-square minimisation of error between the model response and actual system response. However, with the proliferation of highspeed digital computers, elegant and innovative techniques like filter error method, genetic algorithms and artificial neural networks are finding more and more use in parameter estimation problems. Modelling and Parameter Estimation of Dynamic Systems presents a detailed examination of many estimation techniques and modelling problems.
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J.R. Raol has B.E. and M.E. degrees in Electrical Engineering from M.S. University of Baroda, and a Ph.D. from McMaster University, Canada. He is a senior member of the IEEE (USA), life Fellow of the Aeronautical Society of India, life member of the System Society of India and senior scientist with National Aerospace Laboratories (NAL). Dr Raol has written around 100 publications and his research interests include multi-sensor data fusion, parameter estimation and artificial intelligence.
G. Girija has M.Sc. and Ph.D. degrees from Bangalore University and has written around 50 publications. Dr Girija currently works as a senior scientist at NAL, is a recipient of the NAL Foundation Day Award and is a life member of the Aeronautical Society of India. Her research areas are parameter estimation of aerospace vehicles and multi-sensor data fusion.
J. Singh has a Ph.D. in Aerospace Engineering from IIT Kanpur. He is a recipient of the Alexander von Humboldt Fellowship and has worked as a guest scientist at DLR-Institute for Flight Systems, Germany. He is a senior member of the AIAA and a life member of the Aeronautical Society of India and System Society of India. He currently works as a scientist at NAL and is a recipient of the NIL Foundation Day Award. His research areas are aircraft modelling and parameter estimation.
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Hardback. Etat : New. Parameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system dynamics. The assumed model consists of a finite set of parameters, the values of which are calculated using estimation techniques. Most of the techniques that exist are based on least-square minimisation of error between the model response and actual system response. However, with the proliferation of highspeed digital computers, elegant and innovative techniques like filter error method, genetic algorithms and artificial neural networks are finding more and more use in parameter estimation problems. Modelling and Parameter Estimation of Dynamic Systems presents a detailed examination of many estimation techniques and modelling problems. N° de réf. du vendeur LU-9780863413636
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