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Using steady-state prior knowledge to constrain parameter estimates in nonlinear system identification
- Source :
- IEEE Transactions on Circuits and Systems-I: Fundamental Theory.. Sept, 2002, Vol. 49 Issue 9, p1376, 6 p.
- Publication Year :
- 2002
-
Abstract
- This brief investigates the use of prior knowledge in the parameter estimation of NARMAX polynomial models. The problem of parameter estimation is then formulated in such a way that the estimated models have specified features. This formulation results in a constrained optimization problem, which is solved using the ellipsoid algorithm. This technique is applied to a real dc-dc Buck converter. In this system, the static relation is known from the theory but identification data are located over a rather narrow range around an operating point. Although obtained from dynamical data, the models provide good approximation to the nonlinear static function. Index Terms--Grey-box identification, NARMAX models, parameter estimation, prior knowledge.
Details
- ISSN :
- 10577122
- Volume :
- 49
- Issue :
- 9
- Database :
- Gale General OneFile
- Journal :
- IEEE Transactions on Circuits and Systems-I: Fundamental Theory...
- Publication Type :
- Academic Journal
- Accession number :
- edsgcl.92084704