Neuro Fuzzy Type-2 Based Space Vector Modulation for Inverter Fed Induction Motor Drive

In indirect vector control the conventional speed and current controllers operate satisfactory when the operating point is constant. But the operating point is always dynamic, the reference voltages obtained in a closed loop system feding to the inverter contains more harmonics. Due to this the pulses which are going to produce are uneven. Which intern produces the inverter output voltages which are more harmonics contained. In order to produce the better output voltage from the inverter, this paper presents neuro-fuzzy type-2 space vector modulation (NFT2) technique .A performance comparison of the inverter is done with conventional space vector modulation(SVM) and neuro fuzzy type- 1(NFT1) system using matlab simulation & experimental validation. The performance parameters of the induction motor based on current, torque and speed with neuro-fuzzy type-2 space vector modulation is compared with conventional and type-1neuro fuzzy SVM. The % THD of inverter output voltages are also compared .The experimental validation a dspace-1104 is used to analyze performance of induction motor which is obtained by the simulation. The experimental validations are carried out considering 2HP Induction motor in the lab