Indirect Vector Control Drive with PI Controller

Abstract

This paper proposes the neural network solution incorporating an adaptive neuro fuzzy controller to the indirect vector control of three phase induction motor. The basic equations and elements of the indirect vector control scheme are given. The proposed control scheme is realized by using an adaptive neuro-fuzzy controller and two feed forward neural network. The neuro-fuzzy controller incorporates fuzzy logic algorithm with five layer (ANN) structure. The conventional PI controller is replaced by adaptive neuro-fuzzy inference system (ANFIS) which tunes the fuzzy inference system with hybrid learning algorithm. The two feed forward neural network are used as estimator, learned by the Levenberg-Marquardit algorithm with data taken from PI control simulations. The performance of proposed scheme is investigated at different load and speed conditions. The results of the proposed scheme are compared with PI controller. The simulation study shows the robustness and suitability of drive for high performance drive applications.