Title: Model Predictive Control With Weithing Factor Optimization For Torque Ripple Reduction of Induction Machine Fed by Indirect Matrix Converter
Abstract: A finite control set-model predictive control (FCS-MPC) has emerged as a powerful control tool in the field of power converter and drives system. In this dissertation, a novel approach of weighting factor optimization method for reducing the torque ripples of induction machine (IM) fed by indirect matrix converter (IMC) has been introduced and presented. Therefore, an optimization method is adopted here to calculate the optimized weighting factor corresponding to minimum torque ripple of IM. However, model predictive torque and flux control of IM with conventionally selected weighting factor is being investigated in this dissertation and is compared with the proposed optimum weighting factor based MPC control algorithm. Also, model predictive control of IM fed by IMC has been investigated to control the unity power factor at the input of the IMC. MPC control selects the optimized switching state that minimizes a cost function based on optimized weighting factor to actuate the power converter at the next sampling period. The weighting factor optimization method has improved the simulation results by 6% torque ripple of IM at forward high speed, and 10.37% of torque ripple at reverse high speed. On the other hand, at low forward speed, the proposed method has improved the torque ripple by 5.4%, and the improvement at reverse low speed is found as 13.34% of torque ripple. Also, the proposed method has improved the torque ripple by 24.2% (at high speed) and 25% (at low speed) in the experimentation. To achieve the objectives of this dissertation, the issues have been investigated using MATLAB simulation and experimental study in the DS1104 R&D controller platform which proves the robustness of the MPC control and shows potential control tracking of variables with their respective references. Finally, the proposed optimization method has reduced the torque ripples corresponding to conventional weighting factor based MPC control method in this dissertation.
Last Update: 22/11/2022