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This study proposes a robust and powerful finite control set-model predictive control (MPC) algorithm to control the load current with lower total harmonic distortion and efficient reference tracking. In this control, the cost functions are determined for all the possible switching states of the converter and a switching state is selected corresponding to the minimum cost function for actuating the converter in the next sampling time period. To justify the performance of the proposed MPC scheme, a comprehensive study with the carrier-based pulse-width modulation, hysteresis current control and proposed minimum cost function-based MPC of the three-phase load current has been verified in MATLAB Simulink as well as the validation with dSPACE RTI1104 experimentation. This study validates the robustness of the proposed minimum cost function-based MPC control with a RL-load and three-phase induction motor (IM) load. The simulation and experimental results justifies the proposed MPC algorithm with potential tracking of the RL-load current corresponding to the reference current with lower harmonic contents as well as tracking of predictive torque and flux compared to the nominal torque and reference flux of IM, respectively.

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-This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). In this paper, the torque ripple behavior is analyzed to validate the proposed weighting factor optimization method in the predictive control platform and shows the effectiveness of the system. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponds to minimum torque ripple and is compared with the results of conventional weighting factor based predictive control algorithm. The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. The conventional and introduced weighting factor optimization method in predictive control algorithm are validated through simulations and experimental validation in DS1104 R&D controller platform and show the potential control, tracking of variables with their respective references and consequently reduces the torque ripple.

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