6533b873fe1ef96bd12d4aaf
RESEARCH PRODUCT
SM identification of approximating models forH∞ robust control
Mario MilaneseLaura Giarresubject
Observational errorMechanical EngineeringGeneral Chemical EngineeringBiomedical EngineeringNonparametric statisticsAerospace EngineeringIndustrial and Manufacturing EngineeringH-infinity methods in control theoryExponential stabilityControl and Systems EngineeringControl theoryFrequency domainBounded functionApplied mathematicsElectrical and Electronic EngineeringRobust controlParametric statisticsMathematicsdescription
Set Membership (SM) W, identification of mixed parametric and nonparametric models is investigated, aimed to estimate a low order approximating model and an identification error, giving a measure of the unmodeled dynamics in a form well suited for H, control methodologies. In particular, the problem of estimating the parameters of the parametric part and the H, bound on the modeling error is solved using frequency domain data, supposing lbo bounded measurement errors and exponentially stable unmodeled dynamics. The effectiveness of the proposed procedure is tested on some numerical examples, showing the advantages of the proposed methods over the existing nonparametric H, identification approaches are shown, in terms of lower model order and of tightness in the modeling error bounds.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 1999-05-01 | International Journal of Robust and Nonlinear Control |