Performance of Inverter Fed Induction Motor Drive Using Neuro Fuzzy Type-2 Controller

Abstract

The conventional speed and current controllers perform well when the indirect vector control's working point is constant. The operating point, however, is always shifting. In a closed-system situation, the inverter's measured reference voltages show higher harmonics. As a result, the provided pulse is uneven and contains more harmonics, which enables the inverter to create an output voltage that is higher. A space vector modulation technique is presented in this paper for type-2 neuro fuzzy systems (NFT2). The inverter's performance is compared to that of a neuro-fuzzy type-1 (NFT1) system, a neuro-fuzzy type-2 system, and classical space vector modulation (SVM) using Matlab simulation and experimental validation. When using neuro-fuzzy type-2 space vector modulation, the induction motor's performance metrics for current, torque, and speed are compared to those of conventional and neuro-fuzzy type-1 SVM. The performance of an induction motor created by simulation is examined using the experimental validation of a Dspace-1104. The 2 HP induction motor in the lab is taken into consideration in the experimental validations.