State estimation using a model subset and partial model inverse [DC motor control]

Author

Hung, John Y. ; Albritton, Nathaniel G.

Author_Institution

Dept. of Electr. & Comput. Eng., Auburn Univ., AL, USA

Volume

2

fYear

2000

fDate

2000

Firstpage

684

Abstract

A new approach to state estimation is presented. Conditions for existence and a design technique are developed for linear systems. This new technique is compared to conventional full and reduced order observers via simulations in Matlab. As an example problem, a DC motor is chosen as the plant to represent a general electromechanical machine. From this basic model, nonlinearities in magnetics and saturation can be easily added to explore more complicated models. The new technique performs well for certain cases

Keywords

DC motors; control system analysis computing; control system synthesis; electric machine analysis computing; linear systems; machine control; machine theory; observers; DC motor control; Matlab; computer simulation; control design; control simulation; electromechanical machine; linear systems; magnetic nonlinearities; model subset; partial model inverse; saturation nonlinearities; state estimation; Computational modeling; DC motors; Equations; Inverse problems; Linear systems; Magnetics; Mathematical model; Observers; State estimation; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics, 2000. ISIE 2000. Proceedings of the 2000 IEEE International Symposium on

Conference_Location

Cholula, Puebla

Print_ISBN

0-7803-6606-9

Type

conf

DOI

10.1109/ISIE.2000.930380

Filename

930380