Estimation of model error for nonlinear system identification

Raol, JR and Parameswaran, V (1994) Estimation of model error for nonlinear system identification. [["eprint_typename_proceedings" not defined]]

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Algorithms are presented for estimation of deterministic model error in the assumed models of nonlinear discrete and continuous time systems.The explicit model error time histories are parameterized using least squares method. The parameterised models relative to the true model explain the deterministic deficiency in the chosen models, in the sense of minimum model error. The algorithms have appealing features of extended Kalman filter. The numerical simulation results are obtained by implementing the algorithms in PC MATLAB

Item Type: ["eprint_typename_proceedings" not defined]
Additional Information: Copyright for this paper belongs to IEE
Uncontrolled Keywords: Algorithms;Model error;Nonlinear system identification
Subjects: MATHEMATICAL AND COMPUTER SCIENCES > Mathematical and Computer Scienes(General)
Depositing User: M/S ICAST NAL
Date Deposited: 28 Jan 2008
Last Modified: 17 Jun 2010 04:38

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