A small neural network structure application in speed estimation of an induction motor using direct torque control

2006 International Conference on Power Electronic, Drives and Energy Systems

2006

The use of sensorless technologies is an increasing tendency on industrial drivers for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control is used very frequently in order to avoid measurement of all variables involved in this process. The cost reduction may also be considered in industrial drivers, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of artificial neural networks to estimate one of the most important variables in the induction motor control schemes: the speed. Simulation results are presented to validate the proposed approach.

“…The weights associated with the output layer of the network are, therefore, updated using the following relationship: (5) w ji (k + 1) w ji (k) -l OE(k) (2) where:…”

Section: Identification Using Neural Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Speed Estimation for Sensorless Technology Using Recurrent Neural Networks and Single Current Sensor

2006 International Conference on Power Electronic, Drives and Energy Systems

2006

“…The use of sensorless techniques is found mainly in high performance applications like vector-controlled drives and direct torque controlled drivers [1][2][3][4][5][6] and estimators using artificial intelligence [1]. Various approaches were proposed where the speed estimation is based on applied voltage, line current and frequency [14].…”

Section: Introductionmentioning

confidence: 99%

Intelligent System Based Speed Estimation of Induction Motors for Industrial Sensorless Schemes

2007 IEEE International Conference on Control Applications

2007

“…The use of sensorless techniques is found mainly in high performance applications like vector-controlled drives and direct torque controlled drivers [1][2][3][4][5][6]. The main approaches are open-loop estimators using monitored stator and voltage currents, state observers, model reference adaptive systems and estimators using artificial intelligence [1].…”

Section: Introductionmentioning

confidence: 99%

Recurrent Neural Network for Induction Motor Speed Estimation in Industry Applications

MELECON 2006 - 2006 IEEE Mediterranean Electrotechnical Conference

2006

Many electronic drivers for the induction motor control are based on sensorless technologies. The proposal of this work is to present an alternative approach of speed estimation, from transient to steady state, using artificial neural networks. The inputs of the network are the RMS voltage, current and speed estimated of the induction motor feedback to the input with a delay of n samples. Simulation results are also presented to validate the proposed approach.