A modified type-2 neuro-fuzzy SVM-based inverter fed IM drive
by G. Srinivas; G. Durga Sukumar
International Journal of Power Electronics (IJPELEC), Vol. 15, No. 3/4, 2022

Abstract: In indirect vector control, the conventional speed and current controllers operate satisfactorily when the operating point is constant. But the operating point is always dynamic; the reference voltages obtained in a closed-loop system feeding to the inverter contains more harmonics. Due to this, the pulses which are going to produce are uneven and in turn, understudy creates the inverter output voltages produced with more harmonics. In order to produce a better output voltage from the inverter, this paper presents the neuro-fuzzy type-2 (NFT2) space vector modulation technique. Performance comparison of the inverter is done with conventional space vector modulation (SVM) and neuro-fuzzy type-1 (NFT1) system using MATLAB simulation and 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-1 neuro-fuzzy SVM. The % THD of inverter output voltages are also compared. The experimental validation of a DSpace-1104 is used to analyse the performance of the induction motor which is obtained by the simulation. The experimental validations are carried out considering 2HP induction motor in the lab.

Online publication date: Mon, 25-Apr-2022

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