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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Abstract
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: | Journal 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 |
| Division/Department: | Aerospace Electronics and Controls Division, Aerospace Electronics and Controls Division |
| Depositing User: | Mr Vijaianand SK |
| Date Deposited: | 18 Feb 2008 |
| Last Modified: | 24 May 2010 09:38 |
| URI: | http://nal-ir.nal.res.in/id/eprint/329 |
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