Implementation of the direct power control of a doubly fed induction generator by using a Takagi-Sugeno neuro-fuzzy inference system

A Takagi-Sugeno neuro-fuzzy inference system for direct power control of a doubly fed induction generator is presented in this paper. The control variables - d-axis and q-axis rotor voltages - are determined by a control system that consists of a neuro-fuzzy inference system and a first order Takagi-Sugeno fuzzy logic controller. To validate the proposed strategy, experimental tests are made for the DFIG operating speed is slightly less than the synchronous speed. The operation of the generator with abrupt and linear changes in stator power and under variable or constant speeds are tested.