Mr S M Muslem Uddin

Model predictive control (MPC) is a powerful and emerging control algorithm in the field of power converters and energy conversion systems. This paper proposes a model predictive algorithm to control the power flow between the high-voltage and lowvoltage DC buses of a bidirectional isolated full-bridge DC-DC converter. The predictive control algorithm utilises the discrete nature of the power converters and predicts the future nature of the system, which are compared with the references to calculate the cost function. The switching state that minimises the cost function is selected for firing the converter in the next sampling time period. The proposed MPC bidirectional DC-DC converter is simulated with MATLAB/Simulink and further verified with a 2.5 kW experimental configuration. Both the simulation and experimental results confirm that the proposed MPC algorithm of the DC-DC converter reduces reactive power by avoiding the phase shift between primary and secondary sides of the high-frequency transformer and allow power transfer with unity power factor. Finally, an efficiency comparison is performed between the MPC and dualphase-shift-based pulse-width modulation controlled DC-DC converter which ensures the effectiveness of the MPC controller.

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.

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.

Model predictive control has emerged as a powerful control tool in the field of power converter and drive's system. In this article, a weighting factor optimization for reducing the torque ripple of induction machine fed by an indirect matrix converter is introduced and presented. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponding to minimum torque ripple. However, model predictive torque and flux control of the induction machine with conventionally selected weighting factor is being investigated in this article and is compared with the proposed optimum weighting factor based model predictive control algorithm to reduce the torque ripples. The proposed model predictive control scheme utilizes the discrete phenomena of power converter and predicts the future nature of the system variables. For the next sampling period, model predictive method selects the optimized switching state that minimizes a cost function based on optimized weighting factor to actuate the power converter. The introduced weighting factor optimization method in model predictive control algorithm is validated through simulations and shows potential control, tracking of variables with their respective references and consequently reduces the torque ripples corresponding to conventional weighting factor based predictive control method. © 2014 Taylor & Francis Group, LLC.

This paper proposes a delay time compensation method in the model predictive control (MPC) of induction motor (IM) at high and low speed considering the selection of optimum switching vector to actuate the three-phase voltage source inverter (VSI). The proposed control method compensates the delay time to improve the performance of the system, and consequently maintain the accurate tracking of the references at different speed regions. The control scheme utilizes the discrete nature of the system, and uses the possible switching vectors of the converter in an intuitive manner. Therefore, based on minimum quality function the optimum switching vector is selected for the next sampling time actuation of the power converter. The control scheme is validated through the MATLAB simulation and experimental validation in DS1104 R&D Controller Platform. The simulation and experimental results prove the feasibility of the proposed method with encouraging performance.

Boost converter is an essential part of energy storage system for efficient charging of the static devices. This paper proposes a 7.5 kW semi-bridgeless phase-shifted boost converter to improve the efficiency and performance of the energy storage system. This investigation is carried out with the MATLAB Simulink to validate the feasibility of the proposed converter topology. The verification study depicted in this inquisition with the unity power factor and improved efficiency of the converter. The maximum efficiency of the proposed converter is determined as 98.3% for 7.52 kW power transfer at 200 V, 50 Hz input with 70 kHz switching frequency. © 2014 IEEE.

Predictive control is a powerful and promising control algorithm in the control of power converter and electrical machine drive's system. The system performance depends on the selection of weighting factor in the cost function. Therefore, this paper proposed a weighting factor optimization method to reduce the torque ripple of induction motor fed by an indirect matrix converter. Also, predictive torque and flux control with conventional weighting factor is being investigated in this paper and is compared with the proposed optimum weighting factor based predictive control algorithm. The introduced weighting factor optimization method in predictive control algorithm is validated through simulation and shows potential tracking of variables and control with their corresponding references and consequently minimizes the torque ripple compare to the conventional weighting factor based predictive control method. © 2014 IEEE.

A torque and flux FCS-MPC (Finite Control Set Model Predictive Control) of an induction motor with unity power factor fed by an indirect matrix converter has been investigated and presented in this paper. The proposed control scheme utilizes the discrete nature of power converter and predicts the future behavior of the system variables. Also the method selects the switching state that minimizes a cost function to actuate the converter in the next sampling time. The proposed FCS-MPC algorithm is validated through simulations and shows potential control and tracking of variables with their respective references. © 2013 IEEE.

A finite control set model predictive control of an active front end (AFE) rectifier with unity displacement of input voltage and current has been investigated and presented in this paper. In this proposed control algorithm the discrete nature of the power converter are utilized and predicts the future behavior of the input system variables. Also the method selects the switching state that minimizes a cost function for firing the converter in the next sampling period. The proposed predictive control algorithm is validated through simulation and shows potential control and tracking of input unity power factor. © 2013 IEEE.