LSTM-ANN Intelligent Control Based on Space Vector Modulated DTC for Induction Motor Drive
Keywords:
DTC, Induction Motor Drive, LSTM-ANN Controller, SVM.Abstract
DTC, or Direct Torque Control, is an intriguing control method for induction motor drives (IMD) due to its independence from machine rotor parameters. Despite its simplicity, DTC offers effective control of torque steady and transient states. Nevertheless, hysteresis comparators in DTC drives encounter the problem of excessive ripples in torque and inconsistent switching frequency. Conventional DTC, on the other hand, is plagued by significant torque and flux ripples. To tackle this challenge, the widely adopted approach is to incorporate Space Vector Modulation (SVM), which relies on the reference flux and torque. This research paper explores the implementation of LSTM-ANN controllers in conjunction with the SVM method for the inverter. The torque ripple is significantly reduced by the proposed DTC-SVM-IMD system based on LSTM-ANN. To achieve precise speed control, a Fuzzy-PI Controller is employed, while LSTM-ANN duty ratio control is utilized to minimize ripples in flux and torque. The controller's gains are updated by the LSTM-ANN's output, which receives accurate outputs from the speed error and its derivative. This online tuning ensures excellent control performance, even when there are parameter variations and drive non-linearity. The benefits enable the integration of DTC-SVM-IMD with LSTM-ANN for electric vehicles.
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