Time-varying Dynamic Systems Identification

  • Karel J. Keesman
Part of the Advanced Textbooks in Control and Signal Processing book series (C&SP)


Chapter 8 focuses on the recursive parameter estimation of dynamic systems, where, in general, the optimality of the estimation results of the linear regression models of Chap.  7 will no longer hold. Here the interchanging concept of parameter and state will be further worked out, using extended Kalman filtering and observer-based methods. And, again it will be applied to both the linear and nonlinear cases. The theory is illustrated by real-world examples, with most often a biological component in it, as these cases often show a time-varying behavior due to adaptation of the (micro)organisms.


Interpretable Model Structure Transfer Function Model Recursive Estimation Augmented State Vector Recursive Parameter Estimation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Systems and Control GroupWageningen UniversityWageningenNetherlands

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