Abstract
This chapter lays the foundation of the least squares parameter estimation, which allows to determine model parameters from (noisy) measurements. The fundamental method described in this chapter for static non-linear systems will be applied to linear dynamic discrete-time systems in Chap. 9. In Chap. 9, also a recursive formulation will be presented. This allows to identify processes in real time. Several modifications to this basic approach for linear dynamic processes will then be presented in Chap. 10.
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Isermann, R., Münchhof, M. (2011). Least Squares Parameter Estimation for Static Processes. In: Identification of Dynamic Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78879-9_8
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DOI: https://doi.org/10.1007/978-3-540-78879-9_8
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