Time-varying Dynamic Systems Identification

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 


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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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