Summary
Despite the advances in the areas of processing and memory techniques, primarily simple, numerically robust and easily definable methods have been favoured in on-line identification. The principle presented in this paper for combined estimation of state and parameters of linear dynamic systems also has these characteristics. On the one hand, this method is applicable as an adaptive state estimator, on the other hand, because of its small computational effort, the principle used as a parameter estimator presents an alternative to the well known “Recursive Least Squares Method”.
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Bühler, E. (1980). Part I: A Generalisation of the Kalman-Filter-Algorithm and its Application in Optimal Identification Part II: State and Parameter Estimation of Linear Systems in Arbitrary State Coordinates. In: Topics in Identification and Distributed Parameter Systems. Advances in Control Systems and Signal Processing, vol 1. Vieweg+Teubner Verlag, Wiesbaden. https://doi.org/10.1007/978-3-663-13904-1_2
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DOI: https://doi.org/10.1007/978-3-663-13904-1_2
Publisher Name: Vieweg+Teubner Verlag, Wiesbaden
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