Title :
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
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;
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
DOI :
10.1109/ISIE.2000.930380
