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Estimating Parameters of a Dual-rate Observable Canonical System by Combining Kalman Filter and Least Squares Error Method Considering Output through Interpolation and Auxiliary Model | IEEE Conference Publication | IEEE Xplore

Estimating Parameters of a Dual-rate Observable Canonical System by Combining Kalman Filter and Least Squares Error Method Considering Output through Interpolation and Auxiliary Model


Abstract:

In some real practical and industrial applications, output signal sampling and input signal updating are performed with different rates because of technological constrain...Show More

Abstract:

In some real practical and industrial applications, output signal sampling and input signal updating are performed with different rates because of technological constraints. Thus, a large number of existing systems are dual-rate or multi-rate. Identifying parameters of such systems is of great importance. In this paper, we identify parameters of a dual-rate observable canonical system. Since parameters and system states are not known simultaneously, Kalman filter and least squares error method are combined. Parameters are identified with least squares error method and states are estimated using Kalman filter. In this paper, two different algorithms are proposed. In the first algorithm, interpolation is employed to calculate output at instants which are not accessible. In the second algorithm, an auxiliary model is used to obtain output. Finally, in a simulation, parameters of a system are estimated using these algorithms and their results are compared.
Date of Conference: 08-10 May 2018
Date Added to IEEE Xplore: 27 September 2018
ISBN Information:
Conference Location: Mashhad, Iran

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