In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao consider CT system models that are linear in their unknown parameters and propose robust methods of estimation. This book complements the existing literature on the identification of CT systems by enhancing the secondary stage through linear and robust estimation.
In this book, the authors
- provide an overview of CT system identification,
- consider Markov-parameter models and time-moment models as simple linear-in-parameters models for CT system identification,
- bring them into mainstream model parameterization via basis functions,
- present a methodology to robustify the recursive least squares algorithm for parameter estimation of linear regression models,
- suggest a simple off-line error quantification scheme to show that it is possible to quantify error even in the absence of informative priors, and
- indicate some directions for further research.
This modest volume is intended to be a useful addition to the literature on identifying CT systems.
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