The conversion and control for the utilization of power generated from energy sources can be performed using a power electronic converter system. The voltage source inverter (VSI) is one of the commonly used converter topologies, being controlled by a switching control algorithm for power conversion. Finite set-model predictive control (FS-MPC) is a modern switching control algorithm and has received significant attention due to its predictive nature. In this paper, the implementation of FS-MPC is presented for the load-side current control of a three-phase VSI system using an integrated platform of MATLAB/Simulink and Xilinx system generator (XSG). The XSG provides the functionality of digital design and intuitive implementation of field-programmable gate array (FPGA) controlled systems. The additional functionality of hardware-in-the-loop (HIL) co-simulation using FPGA is used for the testing and validation of controller performance. The controller performance is validated through three platforms: MATLAB/Simulink, XSG and HIL co-simulation using ZedBoard Zynq evaluation and development FPGA kit.

In this paper, finite-set model-predictive control (FS-MPC) is inducted for a motor drive system. The dynamic response and multiple constraint handling nature of FS-MPC are the major factors that stand out among the controller family. However, for real-time implementation, the computational burden of FS-MPC is a primary concern. Due to the parallel processing nature and discrete nature of the hardware platform, the field-programmable gate array (FPGA) can be an alternative solution for the real-time implementation of the controller algorithm. The FPGA is capable of handling the computational requirements for FS-MPC implementation; however, the system development involves multiple steps that lead to a time-consuming debugging process. Moreover, specific hardware coding skill makes it more complex, corresponding to an increase in system complexity, which leads to a tedious task for the system development. This paper presents a FPGA-based implementation of the predictive current control of a permanent magnet synchronous motor (PMSM). FS-MPC of the PMSM drive system is designed and implemented using the digital model integration approach provided by the Xilinx system generator (XSG) and VIVADO platform. The step change in the load disturbance as well as the reference speed is considered for the analysis of the controller for the motor drive system. Moreover, the steady state error and harmonic distortion in the motor current is considered for an in-depth analysis of the system performance corresponding to different sampling frequencies.

Finite control set-model predictive control (FCS-MPC) for power electronic systems has been implemented using field-programmable gate array (FPGA) considering an alternative solution to handle the computational burden of the control algorithm. However, FPGA resource utilization is a concern for optimum design and development of the FCS-MPC. This paper presents, an analytical approach based implementation strategies using the Xilinx system generator (XSG) considering the real-time operation of the FCS-MPC for a three-phase voltage source inverter (VSI). Moreover, an adaptive prediction model is proposed to adapt to the change in load current. The percentage THD, dynamic response, and steady-state error are evaluated for system performance analysis. The implementation strategies are compared based on FPGA resource utilization for the FCS-MPC in stationary αβ and rotating dq frames considering fixed, approximated and adaptive values of a coefficient used for current prediction. The look-up tables (LUTs), flip-flops and DSP slices have opted as utilization indices of FPGA resources for comparative analysis. The optimum design based controller model is used for FPGA-based experimental system implementation. The simulation and experimental results are used for the performance evaluation of the FCS-MPC in both αβ and dq frames. Moreover, change in switching state constraint is included in the cost function and controller performance is evaluated corresponding to the weighting factor for approximated and adaptive coefficient values.

Switched-capacitor based multilevel inverter (SC-ML) topologies are gaining attention due to their self-voltage balancing and boosting capabilities. It requires lesser values of DC-link voltage to achieve the desired magnitude of output voltage. Therefore, SC-ML converters significantly contribute for the application of renewable sources especially with solar photovoltaic (PV). Hence, this paper proposed a new three-phase quadruple boost multi-level inverter (QBMLI) topology with switched capacitors for PV applications. The proposed QBMLI generates nine-levels by utilizing two switched capacitors, fewer power electronic switches, and diodes. A level shifted multi-carrier pulse width modulation (PWM) is employed to enhance the quality of output voltage consisting of lower harmonics and high RMS voltages. The proposed topology initially developed in MATLAB/Simulink environment and the per-formance is observed by considering various indices such as modulation index and switching frequency. Furthermore, the system performance is validated in real-time using dSPACE Scalexio based Hardware-in-the-loop (HIL).

Finite set-model predictive control (FS-MPC) is used for power converters and drives having unique advantages as compared to the conventional control strategies. However, the computational burden of the FS-MPC is a primary concern for real-time implementation. Field programmable gate array (FPGA) is an alternative and exciting solution for real-time implementation because of the parallel processing capability, as well as, discrete nature of the hardware platform. Nevertheless, FPGA is capable of handling the computational requirements for the FS-MPC implementation, however, the system development involves multiple steps that lead to the time-consuming debugging process. Moreover, specific hardware coding skill makes it more complex corresponding to an increase in system complexity that leads to a tedious task for system development. This paper presents an FPGA-based experimental implementation of FS-MPC using the system modeling approach. Furthermore, a comparative analysis of FS-MPC in stationary αβ and rotating dq frame is considered for simulation as well as experimental result. The FS-MPC for a three-phase voltage source inverter (VSI) system is developed in a realistic digital simulator integrated with MATLAB-Simulink. The simulated controller model is further used for experimental system implementation and validation using Xilinx FPGA: Zedboard Zynq Evaluation and Development Kit. The digital simulator termed as Xilinx system generator (XSG) provided by Xilinx is used for modeling-based FPGA design.

In this article, the development of multi‐functional grid connected solar photovoltaic (PV) system using improved Fractional order Control theory‐based Pole fixed Second Order Generalized Integrator (FO‐PFSOGI) is proposed. The fractional order (FO) control technique offers an advantage to adjust the fixed structure of the integer order and provide additional degree of freedom to achieve accurate response during the system operation. The FO‐PFSOGI control technique is used to extricate fundamental constituent of the non‐sinusoidal load current. The PV system is competent of feeding the local load requisite and may also inject surplus power into the grid. The voltage source converter (VSC) utilized in the grid‐connected system can also be operated as power quality compensator, taking care of harmonics, unbalancing and excess reactive power demand of the local load. The feasibility of multifunctional operations of the converter is established in this article, thus achieving maximum utilization of the power electronics used in the system and reducing the overall cost. A performance comparison of the developed control technique is presented with the conventional techniques in terms of harmonic compensation, weight convergence and computational complexity. The implementation of the controller is modest and extracts fundamental quantities without any phase delay under different loading conditions. The developed system is validated using both simulation and experimental study. A scaled down experimental setup of grid‐connected PV system is implemented in the laboratory and real time performance of the FO‐PFSOGI is demonstrated using variations in system load and PV irradiance.