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A New Parametric Estimation Algorithm for Large-Scale Systems Described by State-Space Mathematical Models


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DOI: https://doi.org/10.15866/irea.v6i6.16998

Abstract


This paper is concerned with the parametric estimation problem for large-scale systems composed of several interconnected systems, which are described by linear discrete-time state-space mathematical models with unknown parameters. A new recursive parametric estimation algorithm with a particular adaptive gain is proposed for estimating the interconnected system parameters. The stability analysis of the developed parametric estimation scheme is treated by using the Lyapunov method. The proposed recursive parametric estimation algorithm is applied to estimate the parameters of a large-scale systems composed of three interconnected systems. The obtained numerical simulation results show the good performance of this algorithm.
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Keywords


Large-Scale Systems; Interconnected Systems; Parametric Estimation; Recursive Parametric Estimation Algorithm; Discrete-Time State-Space Mathematical Models; Stability

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