TY - GEN
T1 - Auto-associative neural network based sensor drift compensation in indirect vector controlled drive system
AU - Galotto, Luigi
AU - Bose, Bimal K.
AU - Leite, Luciana C.
AU - Pinto, João Onofre Pereira
AU - Da Silva, Luiz Eduardo Borges
AU - Lambert-Torres, Germano
PY - 2007
Y1 - 2007
N2 - The paper proposes an auto-associative neural network (AANN) based sensor drift compensation in an indirect vector-controlled induction motor drive. The feedback signals from the phase current sensors are given as the AANN input. The AANN then performs the auto-associative mapping of these signals so that its output is an estimate of the sensed signals. Since the AANN exploits the physical and analytical redundancy, whenever a sensor starts to drift, the drift is compensated at the output, and the performance of the drive system is barely affected. The paper describes the drive system, gives a brief overview of the AANN, presents the technical approach, and then gives some performance of the system demonstrating validity of the approach. Although current sensors are considered only in the paper, the same approach can be applied to voltage, speed, torque, flux, or any other type sensor.
AB - The paper proposes an auto-associative neural network (AANN) based sensor drift compensation in an indirect vector-controlled induction motor drive. The feedback signals from the phase current sensors are given as the AANN input. The AANN then performs the auto-associative mapping of these signals so that its output is an estimate of the sensed signals. Since the AANN exploits the physical and analytical redundancy, whenever a sensor starts to drift, the drift is compensated at the output, and the performance of the drive system is barely affected. The paper describes the drive system, gives a brief overview of the AANN, presents the technical approach, and then gives some performance of the system demonstrating validity of the approach. Although current sensors are considered only in the paper, the same approach can be applied to voltage, speed, torque, flux, or any other type sensor.
UR - http://www.scopus.com/inward/record.url?scp=49949099639&partnerID=8YFLogxK
U2 - 10.1109/IECON.2007.4460357
DO - 10.1109/IECON.2007.4460357
M3 - Conference contribution
AN - SCOPUS:49949099639
SN - 1424407834
SN - 9781424407835
T3 - IECON Proceedings (Industrial Electronics Conference)
SP - 1009
EP - 1014
BT - Proceedings of the 33rd Annual Conference of the IEEE Industrial Electronics Society, IECON
T2 - 33rd Annual Conference of the IEEE Industrial Electronics Society, IECON
Y2 - 5 November 2007 through 8 November 2007
ER -