This title is available electronically through the IET Digital Library
Author: J. R. Raol, G. Girija and J. Singh
Product Code: PBCE0650
Stock Status: In stock
Scope: 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 minimization of error between the model response and actual system response. However, with the proliferation of high speed digital computers, elegant and innovative techniques like filter error method, H-infinity and Artificial Neural Networks are finding more and more use in parameter estimation problems.
Modelling and Systems Parameter Estimation for Dynamic Systems presents a detailed examination of the estimation techniques and modeling problems. The theory is furnished with several illustrations and computer programs to promote better understanding of system modeling and parameter estimation. The material is presented in a way that makes for easy reading and enables the user to implement and execute the programs himself to gain first hand experience of the estimation process.
To use the programs of SW MODEST, from which the results in the book are generated, please click on the following link; http://www.nal.res.in/modest/index.jsp
"...while this book would be of interest to the general reader, it is of particular appeal to science and engineering students at all levels. It also presents a definite benefit to practising engineers and lecturers who are engaged in parameter estimation work. I found this an enthralling read, which now has a prominent place on my bookshelf - it certainly will be referred to in the future." Karl O. Jones, Measurement & Control, Vol.38, No.8, October 2005
Introduction; Least Squares Methods; Output Error Methods; Filtering Methods; Filter Error Method; Determination of Model Order and Structure; Estimation Before Modelling Approach (EBM); Approach Based on a Concept of Model Error; Parameter Estimation Approaches for Unstable/augmented Systems; Parameter Estimation using ANN and Genetic Algorithms; Online Parameter Estimation; Summary; Appendix A Properties of Signals, Matrices, Estimators and Estimates; Appendix B Aircraft Derivative Models for Parameter Estimation