Online identification of mechanical parameters using extended Kalman filters

Author

Schütte, F. ; Beineke, S. ; Rolfsmeier, A. ; Grotstollen, H.

Author_Institution

Inst. for Power Electron. & Electr. Drives, Paderborn Univ., Germany

Volume

1

fYear

1997

fDate

5-9 Oct 1997

Firstpage

501

Abstract

For the high performance speed and position control of electrical drives featuring elasticity, the observation of nonmeasurable states becomes necessary if only motor speed and current can be measured. In the presence of time-varying inertia or stiffness, online identification of these parameters is also needed, so that controller adaptation becomes feasible. In this paper, extended Kalman filters are applied and optimized for electrical drives modelled as one- or two-mass systems, respectively

Keywords

Kalman filters; control system analysis; filtering theory; machine control; machine theory; motor drives; observers; parameter estimation; position control; velocity control; control simulation; controller adaptation; electrical drives; extended Kalman filters; mechanical parameters identification; one-mass system; online identification; position control; speed control; stiffness; time-varying inertia; two-mass system; Current measurement; Elasticity; Electric variables measurement; Filters; Friction; Nonlinear dynamical systems; Position control; Position measurement; Power measurement; Velocity measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Industry Applications Conference, 1997. Thirty-Second IAS Annual Meeting, IAS '97., Conference Record of the 1997 IEEE

Conference_Location

New Orleans, LA

ISSN

0197-2618

Print_ISBN

0-7803-4067-1

Type

conf

DOI

10.1109/IAS.1997.643069

Filename

643069