Improvement of rotor flux estimation performance of induction motor using Support Vector Machine $\epsilon$-insensitive Regression Method

Support Vector Machine $\epsilon$-insensitive Regression방법을 이용한 유도전동기의 회전자 자속추정 성능개선

In this paper, a novel rotor flux estimation method of an induction motor using support vector machine(SVM) is presented. Two veil-known different flux models with respect to voltage and current are necessary to estimate the rotor flux of an induction motor. The theory of the SVM algorithm is based on statistical teaming theory. Training of SVH leads to a quadratic programming(QP) problem. The proposed SVM rotor flux estimator guarantees the improvement of performance in the transient and steady state in spite of parameter variation circumstance. The validity and the usefulness of Proposed algorithm are throughly verified through numerical simulation.