Adaptive neural network based controller for direct torque control of PMSM with minimum torque ripples and EMI noise reduction

Purpose – The paper aims to provide an adaptive neural network controller for permanent magnet synchronous motor (PMSM) under direct torque control (DTC) algorithm to minimize the torque ripple and EMI noise.Design/methodology/approach – The design methodology is based on vector control used for electrical machines. MATLAB simulations supported with experimental study under C++ are used.Findings – The simulated and experimental results show that considerable torque ripple as well as current ripple and EMI noise reduction can be achieved by utilizing adaptive neural switching algorithm to fire the inverter supplying the PMSM.Research limitations/implications – This research is limited to PMSM, however the research can be extended to include other AC motors as well. In addition, the following points can be studied: the effects of harmonics in control signals on the torque ripple can be analyzed; the actual mathematical relation between the torque and flux ripple can be studied to set the flux and torque ban...

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