Publisher's Synopsis
This book is devoted to identification of Continuous -Time (CT) models which are linear in parameters starting with Markov Parameter and Time Moment models. It explains other linear-in-parameters models - transfer functions represented as Poisson, Lauerre, and Kautz series. To enhance the secondary stage of CT system parameter estimation, linear and robust estimation aspects are discussed. It starts with brief overview of the field of CT system identification followed by Marakov parameters, CT models parameterized with Time Moments of system impulse response function, methodology to robustify the calibrated recursive least squares algorithm for parameter estimation and error quantification. Primarily aimed at researchers and professionals in Control Systems, State Estimation and Optimal Control, Electrical Engineering, Information Science, Automation, it Provides for estimation of system parameters essential for modeling, simulation and control of the system Covers the up-to-date material on parameter identification Simple and clear explanation of the use of basic functions for linear system identification including error quantification Broadens the perspective of the methodology for identification of continuous time systems Developed methodologies can be applied extensively in lab simulation, field experiment and realistic engineering practice
