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The Parameter Compensation Technique of Induction Motor by Neural Network  

Kim Jong-Su (한국해양대학교 선박전자기계공학부)
Oh Sae-Gin (한국해양대학교 운항훈련원)
Kim Sung-Hwan (한국해양대학교 선박전자기계공학부)
Publication Information
Journal of Advanced Marine Engineering and Technology / v.30, no.1, 2006 , pp. 169-175 More about this Journal
Abstract
This paper describes how an Artificial Neural Network(ANN) can be employed to improve a speed estimation in a vector controlled induction motor drive. The system uses the ANN to estimate changes in the motor resistance, which enable the sensorless speed control method to work more accurately. Flux Observer is used for speed estimation in this system. Obviously the accuracy of the speed control of motor is dependent upon how well the parameters of the induction machine are known. These parameters vary with the operating conditions of the motor; both stator resistance(Rs) and rotor resistance(Rr) change with temperature, while the stator leakage inductance varies with load. This paper proposes a parameter compensation technique using artificial neural network for accurate speed estimation of induction motor and simulation results confirm the validity of the proposed scheme.
Keywords
Artificial Neural Network(ANN); Sensorless speed control; Flux Observer;
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  • Reference
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