A Fuzzy Model Reference Learning Controller Based Direct Field Oriented Control of Induction Machine

Abstract

This paper presents a Direct Field Oriented (DFO) induction motor drive system with two distinct features. First, the speed regulation of the proposed drive system is achieved by using a Fuzzy Model Reference Learning Controller (FMRLC), which is more robust and does not require rigorous tuning because of its adaptive nature as compared to the Proportional Integral (PI) and direct fuzzy controllers. Second, a newly designed Sliding Mode Voltage Model Flux Observer (SMVMFO) is incorporated in the drive system to estimate the flux. The proposed SMVMFO is not sensitive to the stator resistance variation which has been a long standing problem in the area of motor drives. Also, it does not require the voltage signal information thus eliminating the need for a voltage sensor. The proposed drive system exhibits better performance because the FMRLC achieves adequate control performance with high-band width speed control and the flux observer guarantees the machines' field orientation thus overcoming the problems of any alteration in the transformation. Extensive simulation results are presented to validate the proposed development and show the effectiveness of the designed drive system.