DocumentCode
3512373
Title
Adaptive neural network-based state filter for induction motor speed estimation
Author
Bharadwaj, Raj Mohan ; Parlos, Alexander G. ; Toliyat, Hamid A.
Author_Institution
Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
Volume
3
fYear
1999
fDate
1999
Firstpage
1283
Abstract
Effective sensorless speed estimation is desirable for both online condition monitoring of induction motors and sensorless adjustable speed AC drive applications. In this paper, the authors present a neural network-based sensorless adaptive speed filter for induction motors. In addition to nameplate information required for the initial set-up, the proposed neural network-based speed filter uses only actual motor currents and voltages. The initial training of the filter helps in obtaining quite acceptable transient speed response from the estimation algorithm. The paper demonstrates the feasibility of adaptive speed filtering for induction motor which could be used for both diagnosis and control purposes
Keywords
adaptive control; condition monitoring; control system analysis; control system synthesis; induction motor drives; machine theory; machine vector control; neurocontrollers; parameter estimation; velocity control; adaptive neural network-based state filter; adjustable speed AC drive applications; induction motor speed estimation; online condition monitoring; sensorless speed estimation; Adaptive control; Adaptive filters; Adaptive systems; Condition monitoring; Induction motors; Information filtering; Information filters; Neural networks; Programmable control; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics Society, 1999. IECON '99 Proceedings. The 25th Annual Conference of the IEEE
Conference_Location
San Jose, CA
Print_ISBN
0-7803-5735-3
Type
conf
DOI
10.1109/IECON.1999.819396
Filename
819396
Link To Document