Estimation of model error for nonlinear system identification

Parameswaran, V and Raol, JR (1994) Estimation of model error for nonlinear system identification. IEE Proceedings: Control Theory and Applications, 141 (6). pp. 403-408.

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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 parameterised 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: Article
Additional Information: Copyright for this article belongs to Institution of Electrical Engineers
Uncontrolled Keywords: Boundary value problems;Computer simulation;Discrete time control systems;Errors;Identification (control systems);Kalman filtering;Least squares approximations; Matrix algebra;Nonlinear systems;Recursive functions; Vectors;Euler-Lagrange equations;Model errors;MATLAB; Algorithms
Subjects: AERONAUTICS > Avionics & Aircraft Instrumentation
Depositing User: Mr Vijaianand SK
Date Deposited: 18 Feb 2008
Last Modified: 24 May 2010 04:08

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